典型工作流示例
本页汇总 DaoAI 天眼系统内置的“模板工作流”示例。可在工作流编辑器中导入、查看并按需调整参数与区域配置。
办公场景
人员离岗检测
用途：识别人员是否离开指定办公区域（离岗/值班空缺）。需在编辑器中配置“监控区域”坐标。
- 组成与流程：
通用检测模型：标签输入
person检测场景中的人员；检测过滤: 过滤出置信度低于0.5的检测结果；
高速追踪：为检测到的对象分配并维护稳定的轨迹/ID，便于持续分析；
区域内存在时间：统计在区域内或者外停留时长；
属性定义: 提取区域内存在时间节点的 离开区域的时间值
time_out_of_zone；条件继续：当停留时长
>= 15秒时，进入后续步骤（可视化/事件保存）；可视化与事件保存:
在图像上绘制“监控区域”多边形与半透明遮罩；
在仪表盘中展示带标注的图像；
保存事件与视频片段。
查看工作流 JSON
1{
2 "name": "离岗检测",
3 "category": "Office",
4 "notes": {
5 "notes_cn": "识别目标人员是否离开指定办公区域，用于监控员工离岗或值班空缺，需要用户自行配置区域坐标。",
6 "notes_en": "Detect whether the target person has left the specified office area, used to monitor employee absenteeism, need to configure the region coordinates by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_obj_det@v1",
19 "name": "general_object_detection_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": [
23 "person"
24 ],
25 "confidence_threshold": 0.5,
26 "label_confidence_thresholds": null,
27 "max_detections": 100
28 },
29 {
30 "type": "core/detections_filter@v1",
31 "name": "detections_filter_1",
32 "comments": null,
33 "predictions": "$steps.detections_filter_2.predictions",
34 "operations": [
35 {
36 "type": "DetectionsFilter",
37 "filter_operation": {
38 "type": "StatementGroup",
39 "statements": [
40 {
41 "type": "BinaryStatement",
42 "left_operand": {
43 "type": "DynamicOperand",
44 "operations": [
45 {
46 "type": "ExtractDetectionProperty",
47 "property_name": "class_name"
48 }
49 ]
50 },
51 "comparator": {
52 "type": "in (Sequence)"
53 },
54 "right_operand": {
55 "type": "StaticOperand",
56 "value": [
57 "person"
58 ]
59 }
60 },
61 {
62 "type": "BinaryStatement",
63 "left_operand": {
64 "type": "DynamicOperand",
65 "operations": [
66 {
67 "type": "ExtractDetectionProperty",
68 "property_name": "confidence"
69 }
70 ]
71 },
72 "comparator": {
73 "type": "(Number) >="
74 },
75 "right_operand": {
76 "type": "StaticOperand",
77 "value": 0.5
78 }
79 }
80 ]
81 }
82 }
83 ],
84 "image": "$inputs.image",
85 "uistate": {
86 "operations": {
87 "filterBy": "class_confidence",
88 "parentClassName": "",
89 "objectClassEnabled": true,
90 "objectClassType": "include",
91 "objectClasses": "person",
92 "attributeEnabled": false,
93 "attributeType": "include",
94 "attributes": "",
95 "confidenceEnabled": true,
96 "confidenceOperator": ">=",
97 "confidenceValue": 0.5,
98 "imageInput": "$inputs.image",
99 "detectionSizeOperator": "<=",
100 "detectionSizeValue": 5,
101 "detectionLocation": "in",
102 "detectionReferencePoint": "center",
103 "zoneDefinition": "Define in Editor",
104 "zonePoints": [],
105 "zoneJson": "[]"
106 }
107 }
108 },
109 {
110 "type": "daoai/event_saver@v1",
111 "name": "event_saver_1",
112 "comments": null,
113 "event_type": "Personnel leaving their posts",
114 "image": "$steps.polygon_zone_visualization_1.image",
115 "original_image": "$inputs.image",
116 "save_video": true,
117 "video_length_seconds": 15,
118 "cooldown_seconds": 20,
119 "cooldown_session_key": null,
120 "per_type_cooldown_seconds": 15
121 },
122 {
123 "type": "core/detections_filter@v1",
124 "name": "detections_filter_2",
125 "comments": null,
126 "predictions": "$steps.general_object_detection_1.predictions",
127 "operations": [
128 {
129 "type": "DetectionsFilter",
130 "filter_operation": {
131 "type": "StatementGroup",
132 "statements": []
133 }
134 }
135 ],
136 "image": "$inputs.image",
137 "uistate": {
138 "operations": {
139 "filterBy": "zone",
140 "parentClassName": "",
141 "objectClassEnabled": false,
142 "objectClassType": "include",
143 "objectClasses": "",
144 "attributeEnabled": false,
145 "attributeType": "include",
146 "attributes": "",
147 "confidenceEnabled": false,
148 "confidenceOperator": ">=",
149 "confidenceValue": 0.5,
150 "imageInput": "$inputs.image",
151 "detectionSizeOperator": "<=",
152 "detectionSizeValue": 5,
153 "detectionLocation": "in",
154 "detectionReferencePoint": "center",
155 "zoneDefinition": "Define in Editor",
156 "zonePoints": [],
157 "zoneJson": "[]"
158 }
159 }
160 },
161 {
162 "type": "daoai/highway_tracker@v1",
163 "name": "highway_tracker_1",
164 "comments": null,
165 "image": "$inputs.image",
166 "detections": "$steps.detections_filter_1.predictions",
167 "track_activation_threshold": 0.5,
168 "lost_track_buffer": 15,
169 "minimum_matching_threshold": 0.3,
170 "minimum_consecutive_frames": 1,
171 "instances_cache_size": 16384
172 },
173 {
174 "type": "daoai/time_out_zone@v1",
175 "name": "time_out_of_zone_1",
176 "comments": null,
177 "image": "$inputs.image",
178 "detections": "$steps.highway_tracker_1.already_seen_instances",
179 "zone": [],
180 "triggering_anchor": "CENTER",
181 "remove_in_zone_detections": true,
182 "target_label": null
183 },
184 {
185 "type": "core/property_definition@v1",
186 "name": "property_definition_1",
187 "comments": null,
188 "data": "$steps.time_out_of_zone_1.timed_detections",
189 "operations": [
190 {
191 "type": "DetectionsPropertyExtract",
192 "property_name": "time_out_of_zone"
193 },
194 {
195 "type": "NumericSequenceAggregate",
196 "function": "max"
197 }
198 ],
199 "image": "$inputs.image"
200 },
201 {
202 "type": "core/continue_if@v1",
203 "name": "continue_if_1",
204 "comments": null,
205 "condition_statement": {
206 "type": "StatementGroup",
207 "statements": [
208 {
209 "type": "BinaryStatement",
210 "left_operand": {
211 "type": "DynamicOperand",
212 "operand_name": "left"
213 },
214 "comparator": {
215 "type": "(Number) >="
216 },
217 "right_operand": {
218 "type": "StaticOperand",
219 "value": 15
220 }
221 }
222 ],
223 "operator": "and",
224 "uistate": {
225 "leftOperand": "$steps.property_definition_1.output",
226 "detectionsEvaluationProperty": "value",
227 "selectedFilterType": "not_selected",
228 "isClassFilteringActive": false,
229 "isAttrFilteringActive": false,
230 "isConfidenceFilteringActive": false,
231 "classSetInclusionMode": "include",
232 "classList": [],
233 "attrList": [],
234 "attrSetInclusionMode": "include",
235 "confidenceThreshold": 0.5,
236 "confidenceOperator": ">=",
237 "referenceImage": null,
238 "sizeThreshold": 5,
239 "sizeThresholdOperator": "<=",
240 "zoneOperator": "in",
241 "zonePoints": [],
242 "detectionReferencePoint": "center",
243 "isZoneStatic": true,
244 "dynamicZone": null,
245 "runtimeParameter": null,
246 "parentClassName": "",
247 "confidenceAggregationMode": "max",
248 "confidenceAggregationOperator": ">=",
249 "confidenceAggregationThreshold": 0.5,
250 "comparator": "(Number) ==",
251 "comparisonType": "Statically",
252 "comparisonValue": "0",
253 "detectionsNumberOperator": "(Number) >=",
254 "detectionsNumberThreshold": 30,
255 "extractedImageProperty": "height",
256 "propertyValueOperator": ">=",
257 "referenceValue": 30,
258 "isReferenceValueStatic": true,
259 "nonImageInputOperation": "(Number) ==",
260 "isMultiLabel": false,
261 "multiLabelOperation": "==",
262 "isFilteringEnabled": false
263 }
264 },
265 "evaluation_parameters": {
266 "left": "$steps.property_definition_1.output"
267 },
268 "next_steps": [
269 "$steps.polygon_zone_visualization_1"
270 ],
271 "image": "$inputs.image"
272 },
273 {
274 "type": "core/polygon_zone_visualization@v1",
275 "name": "polygon_zone_visualization_1",
276 "comments": null,
277 "image": "$inputs.image",
278 "copy_image": true,
279 "zone": [],
280 "color": "#F00",
281 "opacity": 0.3
282 },
283 {
284 "type": "daoai/dashboard_visualization@v1",
285 "name": "dashboard_visualization_1",
286 "comments": null,
287 "image": "$steps.polygon_zone_visualization_1.image"
288 }
289 ],
290 "outputs": [
291 {
292 "type": "JsonField",
293 "name": "event_saver_1_1",
294 "coordinates_system": "own",
295 "selector": "$steps.event_saver_1.error_status"
296 },
297 {
298 "type": "JsonField",
299 "name": "event_saver_1_2",
300 "coordinates_system": "own",
301 "selector": "$steps.event_saver_1.throttling_status"
302 },
303 {
304 "type": "JsonField",
305 "name": "event_saver_1_3",
306 "coordinates_system": "own",
307 "selector": "$steps.event_saver_1.message"
308 },
309 {
310 "type": "JsonField",
311 "name": "event_saver_1_4",
312 "coordinates_system": "own",
313 "selector": "$steps.event_saver_1.image_url"
314 },
315 {
316 "type": "JsonField",
317 "name": "event_saver_1_5",
318 "coordinates_system": "own",
319 "selector": "$steps.event_saver_1.video_url"
320 },
321 {
322 "type": "JsonField",
323 "name": "detections_filter_2_1",
324 "coordinates_system": "own",
325 "selector": "$steps.detections_filter_2.predictions"
326 },
327 {
328 "type": "JsonField",
329 "name": "highway_tracker_1_1",
330 "coordinates_system": "own",
331 "selector": "$steps.highway_tracker_1.tracked_detections"
332 },
333 {
334 "type": "JsonField",
335 "name": "highway_tracker_1_2",
336 "coordinates_system": "own",
337 "selector": "$steps.highway_tracker_1.new_instances"
338 },
339 {
340 "type": "JsonField",
341 "name": "highway_tracker_1_3",
342 "coordinates_system": "own",
343 "selector": "$steps.highway_tracker_1.already_seen_instances"
344 },
345 {
346 "type": "JsonField",
347 "name": "time_out_of_zone_1_1",
348 "coordinates_system": "own",
349 "selector": "$steps.time_out_of_zone_1.timed_detections"
350 },
351 {
352 "type": "JsonField",
353 "name": "property_definition_1_1",
354 "coordinates_system": "own",
355 "selector": "$steps.property_definition_1.output"
356 },
357 {
358 "type": "JsonField",
359 "name": "polygon_zone_visualization_1_1",
360 "coordinates_system": "own",
361 "selector": "$steps.polygon_zone_visualization_1.image"
362 }
363 ]
364 }
365 }
人员聚集检测
用途：识别指定区域内的人员聚集/拥挤情况。
- 组成与流程：
人员检测：标签输入
person检测画面中的人员；区域过滤：在设定区域内筛选检测结果；
条件继续：当区域内人数
>= 4时，进入后续步骤；可视化与事件保存：叠加框与标签并保存事件。
查看工作流 JSON
1{
2 "name": "人员聚集检测",
3 "category": "Office",
4 "notes": {
5 "notes_cn": "根据画面中指定区域内人员数量判断聚集程度，用于识别会议区、公共区域的拥挤或聚集现象，需要用户自行配置区域坐标。",
6 "notes_en": "Determine the degree of crowding based on the size of the people in the image, used to identify the crowded or clustered phenomenon in the meeting area and public area, need to configure the region coordinates by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_obj_det@v1",
19 "name": "general_object_detection_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": [
23 "person"
24 ],
25 "confidence_threshold": null,
26 "label_confidence_thresholds": null,
27 "max_detections": 100
28 },
29 {
30 "type": "core/detections_filter@v1",
31 "name": "detections_filter_1",
32 "comments": null,
33 "predictions": "$steps.general_object_detection_1.predictions",
34 "operations": [
35 {
36 "type": "DetectionsFilter",
37 "filter_operation": {
38 "type": "StatementGroup",
39 "statements": []
40 }
41 }
42 ],
43 "image": "$steps.line_counter_visualization_1.image",
44 "uistate": {
45 "operations": {
46 "filterBy": "zone",
47 "parentClassName": "",
48 "objectClassEnabled": false,
49 "objectClassType": "include",
50 "objectClasses": "",
51 "attributeEnabled": false,
52 "attributeType": "include",
53 "attributes": "",
54 "confidenceEnabled": false,
55 "confidenceOperator": ">=",
56 "confidenceValue": 0.5,
57 "imageInput": "$inputs.image",
58 "detectionSizeOperator": "<=",
59 "detectionSizeValue": 5,
60 "detectionLocation": "in",
61 "detectionReferencePoint": "center",
62 "zoneDefinition": "Define in Editor",
63 "zonePoints": [],
64 "zoneJson": "[]"
65 }
66 }
67 },
68 {
69 "type": "core/continue_if@v1",
70 "name": "continue_if_1",
71 "comments": null,
72 "condition_statement": {
73 "type": "StatementGroup",
74 "statements": [
75 {
76 "type": "BinaryStatement",
77 "left_operand": {
78 "type": "DynamicOperand",
79 "operand_name": "left",
80 "operations": [
81 {
82 "type": "DetectionsFilter",
83 "filter_operation": {
84 "type": "StatementGroup",
85 "operator": "and",
86 "statements": [
87 {
88 "type": "BinaryStatement",
89 "negate": false,
90 "left_operand": {
91 "type": "DynamicOperand",
92 "operand_name": "_",
93 "operations": [
94 {
95 "type": "ExtractDetectionProperty",
96 "property_name": "class_name"
97 }
98 ]
99 },
100 "comparator": {
101 "type": "in (Sequence)"
102 },
103 "right_operand": {
104 "type": "StaticOperand",
105 "value": [
106 "person"
107 ]
108 }
109 }
110 ]
111 }
112 },
113 {
114 "type": "SequenceLength"
115 }
116 ]
117 },
118 "comparator": {
119 "type": "(Number) >="
120 },
121 "right_operand": {
122 "type": "StaticOperand",
123 "value": 4
124 }
125 }
126 ],
127 "operator": "and",
128 "uistate": {
129 "leftOperand": "$steps.detections_filter_1.predictions",
130 "detectionsEvaluationProperty": "detection_count",
131 "selectedFilterType": "class_confidence",
132 "isClassFilteringActive": true,
133 "isAttrFilteringActive": false,
134 "isConfidenceFilteringActive": false,
135 "classSetInclusionMode": "include",
136 "classList": [
137 "person"
138 ],
139 "attrList": [],
140 "attrSetInclusionMode": "include",
141 "confidenceThreshold": 0.5,
142 "confidenceOperator": ">=",
143 "referenceImage": null,
144 "sizeThreshold": 5,
145 "sizeThresholdOperator": "<=",
146 "zoneOperator": "in",
147 "zonePoints": [],
148 "detectionReferencePoint": "center",
149 "isZoneStatic": true,
150 "dynamicZone": null,
151 "runtimeParameter": null,
152 "parentClassName": "",
153 "confidenceAggregationMode": "max",
154 "confidenceAggregationOperator": ">=",
155 "confidenceAggregationThreshold": 0.5,
156 "comparator": "(Number) ==",
157 "comparisonType": "Statically",
158 "comparisonValue": "0",
159 "detectionsNumberOperator": "(Number) >=",
160 "detectionsNumberThreshold": "4",
161 "extractedImageProperty": "height",
162 "propertyValueOperator": ">=",
163 "referenceValue": "4",
164 "isReferenceValueStatic": true,
165 "nonImageInputOperation": "(Number) ==",
166 "isMultiLabel": false,
167 "multiLabelOperation": "==",
168 "isFilteringEnabled": true
169 }
170 },
171 "evaluation_parameters": {
172 "left": "$steps.detections_filter_1.predictions"
173 },
174 "next_steps": [
175 "$steps.event_saver_1"
176 ],
177 "image": "$inputs.image"
178 },
179 {
180 "type": "core/bounding_box_visualization@v1",
181 "name": "bounding_box_visualization_1",
182 "comments": null,
183 "image": "$inputs.image",
184 "copy_image": true,
185 "predictions": "$steps.general_object_detection_1.predictions",
186 "color_palette": "DEFAULT",
187 "palette_size": 10,
188 "custom_colors": [],
189 "color_axis": "CLASS",
190 "thickness": 2,
191 "roundness": 0
192 },
193 {
194 "type": "daoai/event_saver@v1",
195 "name": "event_saver_1",
196 "comments": null,
197 "event_type": "Crowded",
198 "image": "$steps.label_visualization_1.image",
199 "original_image": "$inputs.image",
200 "save_video": true,
201 "video_length_seconds": 30,
202 "cooldown_seconds": 20,
203 "cooldown_session_key": null,
204 "per_type_cooldown_seconds": 30
205 },
206 {
207 "type": "core/label_visualization@v1",
208 "name": "label_visualization_1",
209 "comments": null,
210 "image": "$steps.bounding_box_visualization_1.image",
211 "copy_image": true,
212 "predictions": "$steps.general_object_detection_1.predictions",
213 "color_palette": "DEFAULT",
214 "palette_size": 10,
215 "custom_colors": [],
216 "color_axis": "CLASS",
217 "text": "Class",
218 "text_position": "TOP_LEFT",
219 "text_color": "WHITE",
220 "text_scale": 1,
221 "text_thickness": 1,
222 "text_padding": 10,
223 "border_radius": 0
224 }
225 ],
226 "outputs": [
227 {
228 "name": "detections_filter_1_1",
229 "type": "JsonField",
230 "selector": "$steps.detections_filter_1.predictions"
231 },
232 {
233 "name": "label_visualization_1_1",
234 "type": "JsonField",
235 "selector": "$steps.label_visualization_1.image"
236 }
237 ]
238 }
239
240}
异常行为检测
用途：识别抽烟、打电话、玩手机、摔倒、睡岗、翻越围栏等异常/不当行为（需自训练对应模型）。
- 组成与流程：
行为检测模型：输出异常行为类别与位置；
类别过滤：仅保留目标异常类别；
条件继续：当检测数量
>= 1时，进入后续步骤；可视化与事件保存：绘制框与标签、保存事件并在仪表盘展示。
查看工作流 JSON
1{
2 "name": "异常行为检测",
3 "category": "Office",
4 "notes": {
5 "notes_cn": "检测并识别抽烟、打电话、玩手机、摔倒、睡岗、翻越围栏等不当或异常行为，需要用户使用dw训练对应行为的检测模型",
6 "notes_en": "Detect and identify smoking, calling, playing with mobile phones, falling down, sleeping on duty, crossing fences and other improper or abnormal behaviors, need to use dw to train the detection model for the corresponding behavior."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_detection_model@v1",
19 "name": "general_detection_model_fast_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": ["Abnormal behavior"],
23 "confidence_threshold": null,
24 "label_confidence_thresholds": null,
25 "precision": "fp32",
26 "image_size": "640"
27 },
28 {
29 "type": "core/detections_filter@v1",
30 "name": "detections_filter_1",
31 "comments": null,
32 "predictions": "$steps.general_detection_model_fast_1.predictions",
33 "operations": [
34 {
35 "type": "DetectionsFilter",
36 "filter_operation": {
37 "type": "StatementGroup",
38 "statements": [
39 {
40 "type": "BinaryStatement",
41 "left_operand": {
42 "type": "DynamicOperand",
43 "operations": [
44 {
45 "type": "ExtractDetectionProperty",
46 "property_name": "class_name"
47 }
48 ]
49 },
50 "comparator": {
51 "type": "in (Sequence)"
52 },
53 "right_operand": {
54 "type": "StaticOperand",
55 "value": ["Abnormal behavior"]
56 }
57 }
58 ]
59 }
60 }
61 ],
62 "image": "$inputs.image",
63 "uistate": {
64 "operations": {
65 "filterBy": "class_confidence",
66 "parentClassName": "",
67 "objectClassEnabled": true,
68 "objectClassType": "include",
69 "objectClasses": "Abnormal behavior",
70 "attributeEnabled": false,
71 "attributeType": "include",
72 "attributes": "",
73 "confidenceEnabled": false,
74 "confidenceOperator": ">=",
75 "confidenceValue": 0.5,
76 "imageInput": "$inputs.image",
77 "detectionSizeOperator": "<=",
78 "detectionSizeValue": 5,
79 "detectionLocation": "in",
80 "detectionReferencePoint": "center",
81 "zoneDefinition": "Define in Editor",
82 "zonePoints": [],
83 "zoneJson": "[]"
84 }
85 }
86 },
87 {
88 "type": "core/continue_if@v1",
89 "name": "continue_if_1",
90 "comments": null,
91 "condition_statement": {
92 "type": "StatementGroup",
93 "statements": [
94 {
95 "type": "BinaryStatement",
96 "left_operand": {
97 "type": "DynamicOperand",
98 "operand_name": "left",
99 "operations": [
100 {
101 "type": "SequenceLength"
102 }
103 ]
104 },
105 "comparator": {
106 "type": "(Number) >="
107 },
108 "right_operand": {
109 "type": "StaticOperand",
110 "value": 1
111 }
112 }
113 ],
114 "operator": "and",
115 "uistate": {
116 "leftOperand": "$steps.detections_filter_1.predictions",
117 "detectionsEvaluationProperty": "detection_count",
118 "selectedFilterType": "not_selected",
119 "isClassFilteringActive": false,
120 "isAttrFilteringActive": false,
121 "isConfidenceFilteringActive": false,
122 "classSetInclusionMode": "include",
123 "classList": [],
124 "attrList": [],
125 "attrSetInclusionMode": "include",
126 "confidenceThreshold": 0.5,
127 "confidenceOperator": ">=",
128 "referenceImage": null,
129 "sizeThreshold": 5,
130 "sizeThresholdOperator": "<=",
131 "zoneOperator": "in",
132 "zonePoints": [],
133 "detectionReferencePoint": "center",
134 "isZoneStatic": true,
135 "dynamicZone": null,
136 "runtimeParameter": null,
137 "parentClassName": "",
138 "confidenceAggregationMode": "max",
139 "confidenceAggregationOperator": ">=",
140 "confidenceAggregationThreshold": 0.5,
141 "comparator": "(Number) ==",
142 "comparisonType": "Statically",
143 "comparisonValue": "0",
144 "detectionsNumberOperator": "(Number) >=",
145 "detectionsNumberThreshold": 1,
146 "extractedImageProperty": "height",
147 "propertyValueOperator": ">=",
148 "referenceValue": 1,
149 "isReferenceValueStatic": true,
150 "nonImageInputOperation": "(Number) ==",
151 "isMultiLabel": false,
152 "multiLabelOperation": "==",
153 "isFilteringEnabled": false
154 }
155 },
156 "evaluation_parameters": {
157 "left": "$steps.detections_filter_1.predictions"
158 },
159 "next_steps": ["$steps.bounding_box_visualization_1"],
160 "image": "$inputs.image"
161 },
162 {
163 "type": "core/bounding_box_visualization@v1",
164 "name": "bounding_box_visualization_1",
165 "comments": null,
166 "image": "$inputs.image",
167 "copy_image": true,
168 "predictions": "$steps.general_detection_model_fast_1.predictions",
169 "color_palette": "DEFAULT",
170 "palette_size": 10,
171 "custom_colors": [],
172 "color_axis": "CLASS",
173 "thickness": 2,
174 "roundness": 0
175 },
176 {
177 "type": "core/label_visualization@v1",
178 "name": "label_visualization_1",
179 "comments": null,
180 "image": "$steps.bounding_box_visualization_1.image",
181 "copy_image": true,
182 "predictions": "$steps.general_detection_model_fast_1.predictions",
183 "color_palette": "DEFAULT",
184 "palette_size": 10,
185 "custom_colors": [],
186 "color_axis": "CLASS",
187 "text": "Class",
188 "text_position": "TOP_LEFT",
189 "text_color": "WHITE",
190 "text_scale": 1,
191 "text_thickness": 1,
192 "text_padding": 10,
193 "border_radius": 0
194 },
195 {
196 "type": "daoai/event_saver@v1",
197 "name": "event_saver_1",
198 "comments": null,
199 "event_type": "Abnormal Behavior Detected",
200 "image": "$steps.label_visualization_1.image",
201 "original_image": "$inputs.image",
202 "save_video": true,
203 "video_length_seconds": 30,
204 "cooldown_seconds": 20,
205 "cooldown_session_key": null,
206 "per_type_cooldown_seconds": 30
207 },
208 {
209 "type": "daoai/dashboard_visualization@v1",
210 "name": "dashboard_visualization_1",
211 "comments": null,
212 "image": "$steps.label_visualization_1.image"
213 }
214 ],
215 "outputs": [
216 {
217 "type": "JsonField",
218 "name": "general_detection_model_fast_1_1",
219 "coordinates_system": "own",
220 "selector": "$steps.general_detection_model_fast_1.predictions"
221 },
222 {
223 "type": "JsonField",
224 "name": "detections_filter_1_1",
225 "coordinates_system": "own",
226 "selector": "$steps.detections_filter_1.predictions"
227 },
228 {
229 "type": "JsonField",
230 "name": "bounding_box_visualization_1_1",
231 "coordinates_system": "own",
232 "selector": "$steps.bounding_box_visualization_1.image"
233 },
234 {
235 "type": "JsonField",
236 "name": "label_visualization_1_1",
237 "coordinates_system": "own",
238 "selector": "$steps.label_visualization_1.image"
239 },
240 {
241 "type": "JsonField",
242 "name": "event_saver_1_1",
243 "coordinates_system": "own",
244 "selector": "$steps.event_saver_1.error_status"
245 },
246 {
247 "type": "JsonField",
248 "name": "event_saver_1_2",
249 "coordinates_system": "own",
250 "selector": "$steps.event_saver_1.throttling_status"
251 },
252 {
253 "type": "JsonField",
254 "name": "event_saver_1_3",
255 "coordinates_system": "own",
256 "selector": "$steps.event_saver_1.message"
257 },
258 {
259 "type": "JsonField",
260 "name": "event_saver_1_4",
261 "coordinates_system": "own",
262 "selector": "$steps.event_saver_1.image_url"
263 },
264 {
265 "type": "JsonField",
266 "name": "event_saver_1_5",
267 "coordinates_system": "own",
268 "selector": "$steps.event_saver_1.video_url"
269 }
270 ]
271 }
272}
长时停留检测
用途：统计目标在指定区域内的停留时长，识别过长停留（如长时间玩手机）。
- 组成与流程：
通用检测模型：检测场景中的目标对象；
检测过滤：按需要在设定区域或类别上筛选用于跟踪的检测结果；
目标跟踪：为检测到的对象分配并维护稳定的轨迹/ID；
区域内存在时间：统计在区内停留时长；
属性定义: 提取区域内存在时间节点的 离开区域的时间值
time_in_zone；条件继续：当停留时间达到阈值（示例为
>= 1，实际可在编辑器设定秒数）时，进入后续步骤（可视化/事件保存）；可视化与事件保存：叠加框与“Time In Zone”标签，保存事件与视频片段；
查看工作流 JSON
1{
2 "name": "停留时长检测",
3 "category": "Office",
4 "notes": {
5 "notes_cn": "分析目标在指定区域内的停留时间，用于检测过长停留行为（如长时间玩手机），需要用户自行配置区域坐标。",
6 "notes_en": "Analyze the time spent by the target in the specified area, used to detect long-term stay behavior (such as long-term玩手机), need to configure the region coordinates by yourself."
7 },
8 "definition":{
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/highway_tracker@v1",
19 "name": "highway_tracker_1",
20 "comments": null,
21 "image": "$inputs.image",
22 "detections": "$steps.detections_filter_2.predictions",
23 "track_activation_threshold": 0.25,
24 "lost_track_buffer": 15,
25 "minimum_matching_threshold": 0.3,
26 "minimum_consecutive_frames": 1,
27 "instances_cache_size": 16384
28 },
29 {
30 "type": "core/time_in_zone@v3",
31 "name": "time_in_zone_1",
32 "comments": null,
33 "image": "$inputs.image",
34 "detections": "$steps.highway_tracker_1.tracked_detections",
35 "zone": [],
36 "triggering_anchor": "CENTER",
37 "remove_out_of_zone_detections": true,
38 "reset_out_of_zone_detections": true,
39 "count_out_of_zone_time": false,
40 "count_out_of_image": false,
41 "clear_disappeared_track": false,
42 "clear_disappeared_track_gap_threshold": 8
43 },
44 {
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47 "comments": null,
48 "data": "$steps.time_in_zone_1.timed_detections",
49 "operations": [
50 {
51 "type": "DetectionsPropertyExtract",
52 "property_name": "time_in_zone"
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54 {
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56 "function": "max"
57 }
58 ],
59 "image": "$inputs.image"
60 },
61 {
62 "type": "core/continue_if@v1",
63 "name": "continue_if_1",
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65 "condition_statement": {
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86 "detectionsEvaluationProperty": "value",
87 "selectedFilterType": "not_selected",
88 "isClassFilteringActive": false,
89 "isAttrFilteringActive": false,
90 "isConfidenceFilteringActive": false,
91 "classSetInclusionMode": "include",
92 "classList": [],
93 "attrList": [],
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95 "confidenceThreshold": 0.5,
96 "confidenceOperator": ">=",
97 "referenceImage": null,
98 "sizeThreshold": 5,
99 "sizeThresholdOperator": "<=",
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102 "detectionReferencePoint": "center",
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115 "extractedImageProperty": "height",
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127 },
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131 "image": "$inputs.image"
132 },
133 {
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140 "save_video": true,
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142 "cooldown_seconds": 20,
143 "cooldown_session_key": null,
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146 {
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154 "palette_size": 10,
155 "custom_colors": [],
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160 {
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198 },
199 {
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201 "name": "label_visualization_1",
202 "comments": null,
203 "image": "$steps.bounding_box_visualization_1.image",
204 "copy_image": true,
205 "predictions": "$steps.highway_tracker_1.tracked_detections",
206 "color_palette": "DEFAULT",
207 "palette_size": 10,
208 "custom_colors": [],
209 "color_axis": "CLASS",
210 "text": "Time In Zone",
211 "text_position": "TOP_LEFT",
212 "text_color": "WHITE",
213 "text_scale": 1,
214 "text_thickness": 1,
215 "text_padding": 10,
216 "border_radius": 0
217 },
218 {
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220 "name": "detections_filter_2",
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240 "comparator": {
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242 },
243 "right_operand": {
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245 "value": [
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249 }
250 ]
251 }
252 }
253 ],
254 "image": "$inputs.image",
255 "uistate": {
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258 "parentClassName": "",
259 "objectClassEnabled": true,
260 "objectClassType": "include",
261 "objectClasses": "phone scrolling",
262 "attributeEnabled": false,
263 "attributeType": "include",
264 "attributes": "",
265 "confidenceEnabled": false,
266 "confidenceOperator": ">=",
267 "confidenceValue": 0.5,
268 "imageInput": "$inputs.image",
269 "detectionSizeOperator": "<=",
270 "detectionSizeValue": 5,
271 "detectionLocation": "in",
272 "detectionReferencePoint": "center",
273 "zoneDefinition": "Define in Editor",
274 "zonePoints": [],
275 "zoneJson": "[]"
276 }
277 }
278 },
279 {
280 "type": "daoai/general_obj_det@v1",
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283 "images": "$inputs.image",
284 "classes": [
285 "phone scrolling"
286 ],
287 "confidence_threshold": null,
288 "label_confidence_thresholds": null,
289 "max_detections": 100
290 }
291 ],
292 "outputs": [
293 {
294 "type": "JsonField",
295 "name": "highway_tracker_1_1",
296 "coordinates_system": "own",
297 "selector": "$steps.highway_tracker_1.tracked_detections"
298 },
299 {
300 "type": "JsonField",
301 "name": "highway_tracker_1_2",
302 "coordinates_system": "own",
303 "selector": "$steps.highway_tracker_1.new_instances"
304 },
305 {
306 "type": "JsonField",
307 "name": "highway_tracker_1_3",
308 "coordinates_system": "own",
309 "selector": "$steps.highway_tracker_1.already_seen_instances"
310 },
311 {
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313 "name": "time_in_zone_1_1",
314 "coordinates_system": "own",
315 "selector": "$steps.time_in_zone_1.timed_detections"
316 },
317 {
318 "type": "JsonField",
319 "name": "time_in_zone_1_2",
320 "coordinates_system": "own",
321 "selector": "$steps.time_in_zone_1.disappeared_detections"
322 },
323 {
324 "type": "JsonField",
325 "name": "property_definition_1_1",
326 "coordinates_system": "own",
327 "selector": "$steps.property_definition_1.output"
328 },
329 {
330 "type": "JsonField",
331 "name": "event_saver_1_1",
332 "coordinates_system": "own",
333 "selector": "$steps.event_saver_1.error_status"
334 },
335 {
336 "type": "JsonField",
337 "name": "event_saver_1_2",
338 "coordinates_system": "own",
339 "selector": "$steps.event_saver_1.throttling_status"
340 },
341 {
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343 "name": "event_saver_1_3",
344 "coordinates_system": "own",
345 "selector": "$steps.event_saver_1.message"
346 },
347 {
348 "type": "JsonField",
349 "name": "event_saver_1_4",
350 "coordinates_system": "own",
351 "selector": "$steps.event_saver_1.image_url"
352 },
353 {
354 "type": "JsonField",
355 "name": "event_saver_1_5",
356 "coordinates_system": "own",
357 "selector": "$steps.event_saver_1.video_url"
358 },
359 {
360 "type": "JsonField",
361 "name": "bounding_box_visualization_1_1",
362 "coordinates_system": "own",
363 "selector": "$steps.bounding_box_visualization_1.image"
364 },
365 {
366 "type": "JsonField",
367 "name": "detections_filter_1_1",
368 "coordinates_system": "own",
369 "selector": "$steps.detections_filter_1.predictions"
370 },
371 {
372 "type": "JsonField",
373 "name": "label_visualization_1_1",
374 "coordinates_system": "own",
375 "selector": "$steps.label_visualization_1.image"
376 },
377 {
378 "type": "JsonField",
379 "name": "detections_filter_2_1",
380 "coordinates_system": "own",
381 "selector": "$steps.detections_filter_2.predictions"
382 },
383 {
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385 "name": "general_object_detection_1_1",
386 "coordinates_system": "own",
387 "selector": "$steps.general_object_detection_1.predictions"
388 }
389 ]
390 }
391 }
Highway 场景
交通拥堵检测
用途：结合车辆检测、跟踪与速度估计，识别道路拥堵程度（轻度/中度/重度），并输出事件类型与摘要。
- 组成与流程：
目标检测：检测车、卡车、摩托等对象；
目标跟踪：为车辆分配并维护稳定轨迹/ID；
速度估计：依据标定多边形、方向点与边缘距离计算车速（km/h）；
在区时长：统计车辆在指定区域的停留时间；
拥堵综合分析：融合检测、轨迹、速度与停留信息，计算占用率与拥堵等级，并输出事件类型；
逻辑判断：当拥堵条件为真时继续进入可视化与事件保存；
可视化与事件保存：叠加事件标签、保存图像与视频片段，并可在仪表盘展示。
查看工作流 JSON
1{
2 "name": "交通拥堵检测",
3 "category": "Highway",
4 "notes": {
5 "notes_cn": "结合检测结果的置信度与车辆分布特征，识别道路拥堵程度，并按轻度、中度、重度触发不同级别报警，需要用户自行配置车道信息",
6 "notes_en": "Combine the confidence of detection results and the distribution characteristics of vehicles to identify the degree of road congestion, and trigger different levels of alarms according to light, medium, and heavy congestion."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
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16 "steps": [
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23 "track_activation_threshold": 0.5,
24 "lost_track_buffer": 15,
25 "minimum_matching_threshold": 0.3,
26 "minimum_consecutive_frames": 1,
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28 },
29 {
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31 "name": "highway_speed_1",
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34 "detections": "$steps.highway_tracker_1.already_seen_instances",
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84 "roundness": 0
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86 {
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90 "image": "$steps.bounding_box_visualization_1.image",
91 "copy_image": true,
92 "predictions": "$steps.highway_speed_1.highway_speed_detections",
93 "color_palette": "DEFAULT",
94 "palette_size": 10,
95 "custom_colors": [],
96 "color_axis": "CLASS",
97 "text": "Speed",
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昼夜模型切换
用途：根据时间自动切换白天/夜间检测模型，适应光照变化，保证识别稳定性（需配置模型 UID）。
- 组成与流程：
自定义 Python 模块：根据当前时间输出应使用的模型 UID，；
通用检测：按动态 UID 选择并运行检测模型；
目标跟踪、速度估计、在区时长：与拥堵检测一致，分别统计轨迹、速度与在区停留；
违法/拥堵判定：输出是否违规/拥堵及事件类型；
逻辑判断：当触发条件成立时进入可视化与事件保存；
可视化与事件保存：绘制事件信息并保存图像/视频，支持仪表盘展示。
查看工作流 JSON
1{
2 "name": "昼夜模型切换",
3 "category": "Highway",
4 "notes": {
5 "notes_cn": "根据时间自动切换白天与夜间检测模型，确保在光照变化条件下持续稳定识别，需要用户自行配置模型uid",
6 "notes_en": "Automatically switch between day and night detection models based on time, ensuring continuous and stable recognition under varying lighting conditions, need to configure the model uid by yourself."
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466 "accident_distance_threshold_px": 20,
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498 "count_out_of_zone_time": false,
499 "count_out_of_image": false,
500 "clear_disappeared_track": false,
501 "clear_disappeared_track_gap_threshold": 8
502 },
503 {
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509 },
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515 "value": false
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520 "condition": {
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525 "left_operand": {
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527 "operand_name": "para_1",
528 "operations": []
529 },
530 "comparator": {
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533 "right_operand": {
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535 "value": true
536 }
537 }
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539 },
540 "result": {
541 "type": "StaticCaseResult",
542 "value": true
543 }
544 }
545 ]
546 },
547 "image": "$inputs.image"
548 },
549 {
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551 "name": "continue_if_1",
552 "comments": null,
553 "condition_statement": {
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555 "statements": [
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567 "uistate": {
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569 "detectionsEvaluationProperty": "value",
570 "selectedFilterType": "not_selected",
571 "isClassFilteringActive": false,
572 "isAttrFilteringActive": false,
573 "isConfidenceFilteringActive": false,
574 "classSetInclusionMode": "include",
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577 "attrSetInclusionMode": "include",
578 "confidenceThreshold": 0.5,
579 "confidenceOperator": ">=",
580 "referenceImage": null,
581 "sizeThreshold": 5,
582 "sizeThresholdOperator": "<=",
583 "zoneOperator": "in",
584 "zonePoints": [],
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587 "dynamicZone": null,
588 "runtimeParameter": null,
589 "parentClassName": "",
590 "confidenceAggregationMode": "max",
591 "confidenceAggregationOperator": ">=",
592 "confidenceAggregationThreshold": 0.5,
593 "comparator": "(Number) ==",
594 "comparisonType": "Statically",
595 "comparisonValue": "0",
596 "detectionsNumberOperator": "(Number) >=",
597 "detectionsNumberThreshold": 1,
598 "extractedImageProperty": "height",
599 "propertyValueOperator": ">=",
600 "referenceValue": 1,
601 "isReferenceValueStatic": true,
602 "nonImageInputOperation": "(Number) ==",
603 "isMultiLabel": false,
604 "multiLabelOperation": "==",
605 "isFilteringEnabled": false
606 }
607 },
608 "evaluation_parameters": {
609 "left": "$steps.expression_1.output"
610 },
611 "next_steps": [
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613 ],
614 "image": "$inputs.image"
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616 {
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619 "comments": null,
620 "image": "$inputs.image",
621 "copy_image": true,
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623 "color_palette": "DEFAULT",
624 "palette_size": 10,
625 "custom_colors": [],
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627 "show_event_labels": true,
628 "show_timestamp": true,
629 "show_status_info": true,
630 "bbox_thickness": 4,
631 "roundness": 0,
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633 "text_color": "WHITE",
634 "text_scale": 1,
635 "text_thickness": 1,
636 "text_padding": 10,
637 "border_radius": 0
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639 {
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645 "original_image": "$inputs.image",
646 "save_video": true,
647 "video_length_seconds": 30,
648 "cooldown_seconds": 20,
649 "cooldown_session_key": null,
650 "per_type_cooldown_seconds": 30
651 },
652 {
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656 "image": "$steps.label_visualization_1.image"
657 },
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660 "name": "daoai_world_model_1",
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663 "model_type": "detection",
664 "model_uid": "$steps.DayOrNight.Model_ID",
665 "confidence_threshold": null,
666 "label_confidence_thresholds": null
667 },
668 {
669 "type": "DayOrNight",
670 "name": "DayOrNight"
671 }
672 ],
673 "outputs": [
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676 "name": "highway_tracker_1_1",
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679 },
680 {
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682 "name": "highway_tracker_1_2",
683 "coordinates_system": "own",
684 "selector": "$steps.highway_tracker_1.new_instances"
685 },
686 {
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688 "name": "highway_tracker_1_3",
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690 "selector": "$steps.highway_tracker_1.already_seen_instances"
691 },
692 {
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694 "name": "highway_speed_1_1",
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697 },
698 {
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700 "name": "bounding_box_visualization_1_1",
701 "coordinates_system": "own",
702 "selector": "$steps.bounding_box_visualization_1.image"
703 },
704 {
705 "type": "JsonField",
706 "name": "label_visualization_1_1",
707 "coordinates_system": "own",
708 "selector": "$steps.label_visualization_1.image"
709 },
710 {
711 "type": "JsonField",
712 "name": "highway_detection_1_1",
713 "coordinates_system": "own",
714 "selector": "$steps.highway_detection_1.count"
715 },
716 {
717 "type": "JsonField",
718 "name": "highway_detection_1_2",
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720 "selector": "$steps.highway_detection_1.count_by_label"
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734 {
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740 {
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745 },
746 {
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748 "name": "highway_detection_1_7",
749 "coordinates_system": "own",
750 "selector": "$steps.highway_detection_1.lane_average_speeds"
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752 {
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754 "name": "highway_detection_1_8",
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758 {
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761 "coordinates_system": "own",
762 "selector": "$steps.highway_detection_1.illegal_moving_backward"
763 },
764 {
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768 "selector": "$steps.highway_detection_1.traffic_jam"
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770 {
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776 {
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780 "selector": "$steps.highway_detection_1.occupancy"
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782 {
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794 {
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798 "selector": "$steps.highway_detection_1.violations_detections"
799 },
800 {
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804 "selector": "$steps.highway_detection_1.event_flags"
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806 {
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809 "coordinates_system": "own",
810 "selector": "$steps.highway_detection_1.event_type"
811 },
812 {
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814 "name": "time_in_zone_1_1",
815 "coordinates_system": "own",
816 "selector": "$steps.time_in_zone_1.timed_detections"
817 },
818 {
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820 "name": "time_in_zone_1_2",
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822 "selector": "$steps.time_in_zone_1.disappeared_detections"
823 },
824 {
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827 "coordinates_system": "own",
828 "selector": "$steps.expression_1.output"
829 },
830 {
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832 "name": "highway_visualization_1_1",
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834 "selector": "$steps.highway_visualization_1.image"
835 },
836 {
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839 "coordinates_system": "own",
840 "selector": "$steps.highway_visualization_1.output_image_base64"
841 },
842 {
843 "type": "JsonField",
844 "name": "highway_visualization_1_3",
845 "coordinates_system": "own",
846 "selector": "$steps.highway_visualization_1.image_bytes"
847 },
848 {
849 "type": "JsonField",
850 "name": "highway_visualization_1_4",
851 "coordinates_system": "own",
852 "selector": "$steps.highway_visualization_1.has_violations"
853 },
854 {
855 "type": "JsonField",
856 "name": "highway_visualization_1_5",
857 "coordinates_system": "own",
858 "selector": "$steps.highway_visualization_1.event_summary"
859 },
860 {
861 "type": "JsonField",
862 "name": "event_saver_1_1",
863 "coordinates_system": "own",
864 "selector": "$steps.event_saver_1.error_status"
865 },
866 {
867 "type": "JsonField",
868 "name": "event_saver_1_2",
869 "coordinates_system": "own",
870 "selector": "$steps.event_saver_1.throttling_status"
871 },
872 {
873 "type": "JsonField",
874 "name": "event_saver_1_3",
875 "coordinates_system": "own",
876 "selector": "$steps.event_saver_1.message"
877 },
878 {
879 "type": "JsonField",
880 "name": "event_saver_1_4",
881 "coordinates_system": "own",
882 "selector": "$steps.event_saver_1.image_url"
883 },
884 {
885 "type": "JsonField",
886 "name": "event_saver_1_5",
887 "coordinates_system": "own",
888 "selector": "$steps.event_saver_1.video_url"
889 },
890 {
891 "type": "JsonField",
892 "name": "daoai_world_model_1_1",
893 "coordinates_system": "own",
894 "selector": "$steps.daoai_world_model_1.predictions"
895 },
896 {
897 "type": "JsonField",
898 "name": "Model_ID",
899 "coordinates_system": "own",
900 "selector": "$steps.DayOrNight.Model_ID"
901 }
902 ],
903 "dynamic_blocks_definitions": [
904 {
905 "type": "DynamicBlockDefinition",
906 "manifest": {
907 "type": "ManifestDescription",
908 "description": "Switch Detection Models to Fit Sunlight or Darkness",
909 "block_type": "DayOrNight",
910 "inputs": {},
911 "outputs": {
912 "Model_ID": {
913 "type": "DynamicOutputDefinition",
914 "kind": [
915 "string"
916 ]
917 }
918 }
919 },
920 "code": {
921 "type": "PythonCode",
922 "run_function_code": "from datetime import datetime, time\n\ndef run(self) -> BlockResult:\n # 配置两个模型 ID：17:00 前和 17:00 后\n before_5_id = \"WLpN-BCURwfYmd4vSqXYtQ\"\n after_5_id = \"j581of38O0XluvWUHY1-xw\"\n\n now = datetime.now()\n five_pm = time(23, 5)\n model_id = \"\"\n if now.time() < five_pm:\n model_id = before_5_id\n else:\n model_id = after_5_id\n return {\"Model_ID\": model_id}"
923 }
924 }
925 ]
926 }
927}
车速与行驶轨迹检测
用途：实时检测车辆速度并分析行驶轨迹，用于识别超速、异常减速、逆行、频繁变道等行为，辅助交通安全监管。
- 组成与流程：
目标检测：检测车、卡车、摩托等对象；
目标跟踪：维护稳定的车辆轨迹/ID；
速度估计：通过标定与方向点计算车速；
在区时长：统计在指定车道或区域的停留时间；
违规/轨迹分析：综合速度、轨迹与停留信息识别超速、逆行、异常变道等；
逻辑判断：当违规条件为真时进入可视化与事件保存；
可视化与事件保存：叠加事件标签，保存图像/视频，并可在仪表盘展示。
查看工作流 JSON
1{
2 "name": "车速检测,行驶轨迹检测",
3 "category": "Highway",
4 "notes": {
5 "notes_cn": "实时检测高速路上车辆的速度，用于识别超速、异常减速等行为，辅助交通安全监管。并且分析高速路上车辆的行驶轨迹，用于识别异常变道、逆行、频繁蛇形驾驶等行为，需要用户自行配置车道信息",
6 "notes_en": "Real-time detection of vehicle speed on highways, used to identify speeding, abnormal deceleration, and other behaviors, and to analyze the driving trajectory of vehicles on highways, used to identify abnormal lane changes,逆行, frequent snake driving, etc., need to configure the lane information by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/highway_tracker@v1",
19 "name": "highway_tracker_1",
20 "comments": null,
21 "image": "$inputs.image",
22 "detections": "$steps.general_detection_model_fast_1.predictions",
23 "track_activation_threshold": 0.5,
24 "lost_track_buffer": 15,
25 "minimum_matching_threshold": 0.3,
26 "minimum_consecutive_frames": 1,
27 "instances_cache_size": 16384
28 },
29 {
30 "type": "daoai/highway_speed@v1",
31 "name": "highway_speed_1",
32 "comments": null,
33 "image": "$inputs.image",
34 "detections": "$steps.highway_tracker_1.already_seen_instances",
35 "calibration_polygon": [
36 [
37 1025.3333333333337,
38 318.6666666666667
39 ],
40 [
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43 ],
44 [
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47 ],
48 [
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51 ]
52 ],
53 "edge_distances": [
54 20,
55 200,
56 20,
57 200
58 ],
59 "direction_points": [
60 [
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63 ],
64 [
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67 ]
68 ],
69 "output_unit": "kmh",
70 "smoothing_alpha": 0.5
71 },
72 {
73 "type": "core/bounding_box_visualization@v1",
74 "name": "bounding_box_visualization_1",
75 "comments": null,
76 "image": "$inputs.image",
77 "copy_image": true,
78 "predictions": "$steps.highway_tracker_1.tracked_detections",
79 "color_palette": "DEFAULT",
80 "palette_size": 10,
81 "custom_colors": [],
82 "color_axis": "CLASS",
83 "thickness": 2,
84 "roundness": 0
85 },
86 {
87 "type": "core/label_visualization@v1",
88 "name": "label_visualization_1",
89 "comments": null,
90 "image": "$steps.bounding_box_visualization_1.image",
91 "copy_image": true,
92 "predictions": "$steps.highway_speed_1.highway_speed_detections",
93 "color_palette": "DEFAULT",
94 "palette_size": 10,
95 "custom_colors": [],
96 "color_axis": "CLASS",
97 "text": "Speed",
98 "text_position": "TOP_LEFT",
99 "text_color": "WHITE",
100 "text_scale": 1,
101 "text_thickness": 1,
102 "text_padding": 10,
103 "border_radius": 0
104 },
105 {
106 "type": "daoai/highway_detection@v1",
107 "name": "highway_detection_1",
108 "comments": null,
109 "image": "$inputs.image",
110 "model_predictions": "$steps.general_detection_model_fast_1.predictions",
111 "tracked_detections": "$steps.highway_tracker_1.tracked_detections",
112 "velocity_detections": "$steps.highway_speed_1.highway_speed_detections",
113 "timed_detections": "$steps.time_in_zone_1.timed_detections",
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Construction Site 场景
工地热人数统计
用途：统计画面中人员数量，便于了解现场人员密度与热度。
- 组成与流程：
目标检测：检测人员；
检测过滤：仅保留人员且置信度 >= 0.5；
属性提取：计算检测数量用于事件类型或展示；
可视化与事件保存：叠加框与标签，按人数保存事件与视频片段。
查看工作流 JSON
1{
2 "name": "工地热人数统计",
3 "category": "Construction Site",
4 "notes": {
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6 "notes_en": "Use the general detection model to detect the number of people in the area of the image."
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152 "border_radius": 0
153 },
154 {
155 "type": "daoai/event_saver@v1",
156 "name": "event_saver_1",
157 "comments": null,
158 "event_type": "$steps.property_definition_1.output",
159 "image": "$steps.label_visualization_1.image",
160 "original_image": "$inputs.image",
161 "save_video": true,
162 "video_length_seconds": 30,
163 "cooldown_seconds": 20,
164 "cooldown_session_key": null,
165 "per_type_cooldown_seconds": 30
166 }
167 ],
168 "outputs": [
169 {
170 "name": "property_definition_1_1",
171 "type": "JsonField",
172 "selector": "$steps.property_definition_1.output"
173 },
174 {
175 "name": "label_visualization_1",
176 "type": "JsonField",
177 "selector": "$steps.label_visualization_1.image"
178 },
179 {
180 "type": "JsonField",
181 "name": "event_saver_1_1",
182 "coordinates_system": "own",
183 "selector": "$steps.event_saver_1.error_status"
184 },
185 {
186 "type": "JsonField",
187 "name": "event_saver_1_2",
188 "coordinates_system": "own",
189 "selector": "$steps.event_saver_1.throttling_status"
190 },
191 {
192 "type": "JsonField",
193 "name": "event_saver_1_3",
194 "coordinates_system": "own",
195 "selector": "$steps.event_saver_1.message"
196 },
197 {
198 "type": "JsonField",
199 "name": "event_saver_1_4",
200 "coordinates_system": "own",
201 "selector": "$steps.event_saver_1.image_url"
202 },
203 {
204 "type": "JsonField",
205 "name": "event_saver_1_5",
206 "coordinates_system": "own",
207 "selector": "$steps.event_saver_1.video_url"
208 }
209 ]
210 }
211 }
区域占用检测
用途：检测指定区域是否被物体占用（车、卡车、摩托、大件物品等），需在编辑器配置区域坐标。
- 组成与流程：
目标检测：检测目标类别；
区域过滤：在目标区域筛选检测结果；
目标跟踪：维护稳定轨迹与 ID；
条件继续：当区域内存在目标（数量 >= 1）进入可视化与事件保存；
可视化与事件保存：绘制框与标签并保存事件。
查看工作流 JSON
1{
2 "name": "区域占用检测",
3 "category": "Construction Site",
4 "notes": {
5 "notes_cn": "使用通用目标检测模型检测图片指定区域中是否被占用，需要用户自行配置区域坐标。",
6 "notes_en": "Use the general detection model to detect whether the specified area of the image is occupied, need to configure the region coordinates by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_obj_det@v1",
19 "name": "general_object_detection_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": [
23 "car",
24 "truck",
25 "motorcycle",
26 "large item"
27 ],
28 "confidence_threshold": 0.5,
29 "label_confidence_thresholds": null,
30 "max_detections": 100
31 },
32 {
33 "type": "daoai/highway_tracker@v1",
34 "name": "highway_tracker_1",
35 "comments": null,
36 "image": "$inputs.image",
37 "detections": "$steps.detections_filter_1.predictions",
38 "track_activation_threshold": 0.5,
39 "lost_track_buffer": 15,
40 "minimum_matching_threshold": 0.3,
41 "minimum_consecutive_frames": 1,
42 "instances_cache_size": 16384
43 },
44 {
45 "type": "daoai/event_saver@v1",
46 "name": "event_saver_1",
47 "comments": null,
48 "event_type": "Region Occupied",
49 "image": "$steps.label_visualization_1.image",
50 "original_image": "$inputs.image",
51 "save_video": true,
52 "video_length_seconds": 30,
53 "cooldown_seconds": 20,
54 "cooldown_session_key": null,
55 "per_type_cooldown_seconds": 30
56 },
57 {
58 "type": "core/bounding_box_visualization@v1",
59 "name": "bounding_box_visualization_1",
60 "comments": null,
61 "image": "$inputs.image",
62 "copy_image": true,
63 "predictions": "$steps.highway_tracker_1.tracked_detections",
64 "color_palette": "DEFAULT",
65 "palette_size": 10,
66 "custom_colors": [],
67 "color_axis": "CLASS",
68 "thickness": 2,
69 "roundness": 0
70 },
71 {
72 "type": "core/detections_filter@v1",
73 "name": "detections_filter_1",
74 "comments": null,
75 "predictions": "$steps.general_object_detection_1.predictions",
76 "operations": [
77 {
78 "type": "DetectionsFilter",
79 "filter_operation": {
80 "type": "StatementGroup",
81 "statements": []
82 }
83 }
84 ],
85 "image": "$inputs.image",
86 "uistate": {
87 "operations": {
88 "filterBy": "zone",
89 "parentClassName": "",
90 "objectClassEnabled": false,
91 "objectClassType": "include",
92 "objectClasses": "",
93 "attributeEnabled": false,
94 "attributeType": "include",
95 "attributes": "",
96 "confidenceEnabled": false,
97 "confidenceOperator": ">=",
98 "confidenceValue": 0.5,
99 "imageInput": "$inputs.image",
100 "detectionSizeOperator": "<=",
101 "detectionSizeValue": 5,
102 "detectionLocation": "in",
103 "detectionReferencePoint": "center",
104 "zoneDefinition": "Define in Editor",
105 "zonePoints": [],
106 "zoneJson": "[]"
107 }
108 }
109 },
110 {
111 "type": "core/label_visualization@v1",
112 "name": "label_visualization_1",
113 "comments": null,
114 "image": "$steps.bounding_box_visualization_1.image",
115 "copy_image": true,
116 "predictions": "$steps.highway_tracker_1.tracked_detections",
117 "color_palette": "DEFAULT",
118 "palette_size": 10,
119 "custom_colors": [],
120 "color_axis": "CLASS",
121 "text": "Class",
122 "text_position": "TOP_LEFT",
123 "text_color": "WHITE",
124 "text_scale": 1,
125 "text_thickness": 1,
126 "text_padding": 10,
127 "border_radius": 0
128 },
129 {
130 "type": "core/continue_if@v1",
131 "name": "continue_if_1",
132 "comments": null,
133 "condition_statement": {
134 "type": "StatementGroup",
135 "statements": [
136 {
137 "type": "BinaryStatement",
138 "left_operand": {
139 "type": "DynamicOperand",
140 "operand_name": "left",
141 "operations": [
142 {
143 "type": "SequenceLength"
144 }
145 ]
146 },
147 "comparator": {
148 "type": "(Number) >="
149 },
150 "right_operand": {
151 "type": "StaticOperand",
152 "value": 1
153 }
154 }
155 ],
156 "operator": "and",
157 "uistate": {
158 "leftOperand": "$steps.highway_tracker_1.tracked_detections",
159 "detectionsEvaluationProperty": "detection_count",
160 "selectedFilterType": "not_selected",
161 "isClassFilteringActive": false,
162 "isAttrFilteringActive": false,
163 "isConfidenceFilteringActive": false,
164 "classSetInclusionMode": "include",
165 "classList": [],
166 "attrList": [],
167 "attrSetInclusionMode": "include",
168 "confidenceThreshold": 0.5,
169 "confidenceOperator": ">=",
170 "referenceImage": null,
171 "sizeThreshold": 5,
172 "sizeThresholdOperator": "<=",
173 "zoneOperator": "in",
174 "zonePoints": [],
175 "detectionReferencePoint": "center",
176 "isZoneStatic": true,
177 "dynamicZone": null,
178 "runtimeParameter": null,
179 "parentClassName": "",
180 "confidenceAggregationMode": "max",
181 "confidenceAggregationOperator": ">=",
182 "confidenceAggregationThreshold": 0.5,
183 "comparator": "(Number) ==",
184 "comparisonType": "Statically",
185 "comparisonValue": "0",
186 "detectionsNumberOperator": "(Number) >=",
187 "detectionsNumberThreshold": 1,
188 "extractedImageProperty": "height",
189 "propertyValueOperator": ">=",
190 "referenceValue": 1,
191 "isReferenceValueStatic": true,
192 "nonImageInputOperation": "(Number) ==",
193 "isMultiLabel": false,
194 "multiLabelOperation": "==",
195 "isFilteringEnabled": false
196 }
197 },
198 "evaluation_parameters": {
199 "left": "$steps.highway_tracker_1.tracked_detections"
200 },
201 "next_steps": [
202 "$steps.bounding_box_visualization_1"
203 ],
204 "image": "$inputs.image"
205 }
206 ],
207 "outputs": [
208 {
209 "type": "JsonField",
210 "name": "general_object_detection_1_1",
211 "coordinates_system": "own",
212 "selector": "$steps.general_object_detection_1.predictions"
213 },
214 {
215 "type": "JsonField",
216 "name": "highway_tracker_1_1",
217 "coordinates_system": "own",
218 "selector": "$steps.highway_tracker_1.tracked_detections"
219 },
220 {
221 "type": "JsonField",
222 "name": "highway_tracker_1_2",
223 "coordinates_system": "own",
224 "selector": "$steps.highway_tracker_1.new_instances"
225 },
226 {
227 "type": "JsonField",
228 "name": "highway_tracker_1_3",
229 "coordinates_system": "own",
230 "selector": "$steps.highway_tracker_1.already_seen_instances"
231 },
232 {
233 "type": "JsonField",
234 "name": "event_saver_1_1",
235 "coordinates_system": "own",
236 "selector": "$steps.event_saver_1.error_status"
237 },
238 {
239 "type": "JsonField",
240 "name": "event_saver_1_2",
241 "coordinates_system": "own",
242 "selector": "$steps.event_saver_1.throttling_status"
243 },
244 {
245 "type": "JsonField",
246 "name": "event_saver_1_3",
247 "coordinates_system": "own",
248 "selector": "$steps.event_saver_1.message"
249 },
250 {
251 "type": "JsonField",
252 "name": "event_saver_1_4",
253 "coordinates_system": "own",
254 "selector": "$steps.event_saver_1.image_url"
255 },
256 {
257 "type": "JsonField",
258 "name": "event_saver_1_5",
259 "coordinates_system": "own",
260 "selector": "$steps.event_saver_1.video_url"
261 },
262 {
263 "type": "JsonField",
264 "name": "bounding_box_visualization_1_1",
265 "coordinates_system": "own",
266 "selector": "$steps.bounding_box_visualization_1.image"
267 },
268 {
269 "type": "JsonField",
270 "name": "detections_filter_1_1",
271 "coordinates_system": "own",
272 "selector": "$steps.detections_filter_1.predictions"
273 },
274 {
275 "type": "JsonField",
276 "name": "label_visualization_1_1",
277 "coordinates_system": "own",
278 "selector": "$steps.label_visualization_1.image"
279 }
280 ]
281 }
282 }
作业区人员距离检测
用途：检测危险/作业区域是否有人员靠近，辅助安全管控；需在编辑器配置区域坐标。
- 组成与流程：
目标检测：检测人员（staff）；
区域过滤：在危险区域筛选检测结果；
条件继续：当区域内存在人员（数量 >= 1）进入可视化；
可视化与事件保存：绘制框与标签并保存事件与视频。
查看工作流 JSON
1{
2 "name": "作业区人员距离检测",
3 "category": "Construction Site",
4 "notes": {
5 "notes_cn": "使用通用目标检测模型检测图片危险区域中是否有人员靠近，需要用户自行配置区域坐标。",
6 "notes_en": "Use the general detection model to detect whether there is a person in the danger area of the image, need to configure the region coordinates by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_obj_det@v1",
19 "name": "general_object_detection_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": [
23 "staff"
24 ],
25 "confidence_threshold": 0.5,
26 "label_confidence_thresholds": null,
27 "max_detections": 100
28 },
29 {
30 "type": "daoai/event_saver@v1",
31 "name": "event_saver_1",
32 "comments": null,
33 "event_type": "Staff Detected in Danger Zone",
34 "image": "$steps.label_visualization_1.image",
35 "original_image": "$inputs.image",
36 "save_video": true,
37 "video_length_seconds": 30,
38 "cooldown_seconds": 20,
39 "cooldown_session_key": null,
40 "per_type_cooldown_seconds": 30
41 },
42 {
43 "type": "core/detections_filter@v1",
44 "name": "detections_filter_1",
45 "comments": null,
46 "predictions": "$steps.general_object_detection_1.predictions",
47 "operations": [
48 {
49 "type": "DetectionsFilter",
50 "filter_operation": {
51 "type": "StatementGroup",
52 "statements": []
53 }
54 }
55 ],
56 "image": "$inputs.image",
57 "uistate": {
58 "operations": {
59 "filterBy": "zone",
60 "parentClassName": "",
61 "objectClassEnabled": false,
62 "objectClassType": "include",
63 "objectClasses": "",
64 "attributeEnabled": false,
65 "attributeType": "include",
66 "attributes": "",
67 "confidenceEnabled": false,
68 "confidenceOperator": ">=",
69 "confidenceValue": 0.5,
70 "imageInput": "$inputs.image",
71 "detectionSizeOperator": "<=",
72 "detectionSizeValue": 5,
73 "detectionLocation": "in",
74 "detectionReferencePoint": "center",
75 "zoneDefinition": "Define in Editor",
76 "zonePoints": [],
77 "zoneJson": "[]"
78 }
79 }
80 },
81 {
82 "type": "core/continue_if@v1",
83 "name": "continue_if_1",
84 "comments": null,
85 "condition_statement": {
86 "type": "StatementGroup",
87 "statements": [
88 {
89 "type": "BinaryStatement",
90 "left_operand": {
91 "type": "DynamicOperand",
92 "operand_name": "left",
93 "operations": [
94 {
95 "type": "SequenceLength"
96 }
97 ]
98 },
99 "comparator": {
100 "type": "(Number) >="
101 },
102 "right_operand": {
103 "type": "StaticOperand",
104 "value": 1
105 }
106 }
107 ],
108 "operator": "and",
109 "uistate": {
110 "leftOperand": "$steps.detections_filter_2.predictions",
111 "detectionsEvaluationProperty": "detection_count",
112 "selectedFilterType": "not_selected",
113 "isClassFilteringActive": true,
114 "isAttrFilteringActive": false,
115 "isConfidenceFilteringActive": true,
116 "classSetInclusionMode": "include",
117 "classList": [
118 "staff"
119 ],
120 "attrList": [],
121 "attrSetInclusionMode": "include",
122 "confidenceThreshold": 0.5,
123 "confidenceOperator": ">=",
124 "referenceImage": null,
125 "sizeThreshold": 5,
126 "sizeThresholdOperator": "<=",
127 "zoneOperator": "in",
128 "zonePoints": [],
129 "detectionReferencePoint": "center",
130 "isZoneStatic": true,
131 "dynamicZone": null,
132 "runtimeParameter": null,
133 "parentClassName": "",
134 "confidenceAggregationMode": "max",
135 "confidenceAggregationOperator": ">=",
136 "confidenceAggregationThreshold": 0.5,
137 "comparator": "(Number) ==",
138 "comparisonType": "Statically",
139 "comparisonValue": "0",
140 "detectionsNumberOperator": "(Number) >=",
141 "detectionsNumberThreshold": 1,
142 "extractedImageProperty": "height",
143 "propertyValueOperator": ">=",
144 "referenceValue": 1,
145 "isReferenceValueStatic": true,
146 "nonImageInputOperation": "(Number) ==",
147 "isMultiLabel": false,
148 "multiLabelOperation": "==",
149 "isFilteringEnabled": false
150 }
151 },
152 "evaluation_parameters": {
153 "left": "$steps.detections_filter_2.predictions"
154 },
155 "next_steps": [
156 "$steps.bounding_box_visualization_1"
157 ],
158 "image": "$inputs.image"
159 },
160 {
161 "type": "core/bounding_box_visualization@v1",
162 "name": "bounding_box_visualization_1",
163 "comments": null,
164 "image": "$inputs.image",
165 "copy_image": true,
166 "predictions": "$steps.detections_filter_2.predictions",
167 "color_palette": "DEFAULT",
168 "palette_size": 10,
169 "custom_colors": [],
170 "color_axis": "CLASS",
171 "thickness": 2,
172 "roundness": 0
173 },
174 {
175 "type": "core/detections_filter@v1",
176 "name": "detections_filter_2",
177 "comments": null,
178 "predictions": "$steps.detections_filter_1.predictions",
179 "operations": [
180 {
181 "type": "DetectionsFilter",
182 "filter_operation": {
183 "type": "StatementGroup",
184 "statements": [
185 {
186 "type": "BinaryStatement",
187 "left_operand": {
188 "type": "DynamicOperand",
189 "operations": [
190 {
191 "type": "ExtractDetectionProperty",
192 "property_name": "class_name"
193 }
194 ]
195 },
196 "comparator": {
197 "type": "in (Sequence)"
198 },
199 "right_operand": {
200 "type": "StaticOperand",
201 "value": [
202 "staff"
203 ]
204 }
205 },
206 {
207 "type": "BinaryStatement",
208 "left_operand": {
209 "type": "DynamicOperand",
210 "operations": [
211 {
212 "type": "ExtractDetectionProperty",
213 "property_name": "confidence"
214 }
215 ]
216 },
217 "comparator": {
218 "type": "(Number) >="
219 },
220 "right_operand": {
221 "type": "StaticOperand",
222 "value": 0.5
223 }
224 }
225 ]
226 }
227 }
228 ],
229 "image": "$inputs.image",
230 "uistate": {
231 "operations": {
232 "filterBy": "class_confidence",
233 "parentClassName": "",
234 "objectClassEnabled": true,
235 "objectClassType": "include",
236 "objectClasses": "staff",
237 "attributeEnabled": false,
238 "attributeType": "include",
239 "attributes": "",
240 "confidenceEnabled": true,
241 "confidenceOperator": ">=",
242 "confidenceValue": 0.5,
243 "imageInput": "$inputs.image",
244 "detectionSizeOperator": "<=",
245 "detectionSizeValue": 5,
246 "detectionLocation": "in",
247 "detectionReferencePoint": "center",
248 "zoneDefinition": "Define in Editor",
249 "zonePoints": [],
250 "zoneJson": "[]"
251 }
252 }
253 },
254 {
255 "type": "core/label_visualization@v1",
256 "name": "label_visualization_1",
257 "comments": null,
258 "image": "$steps.bounding_box_visualization_1.image",
259 "copy_image": true,
260 "predictions": "$steps.detections_filter_2.predictions",
261 "color_palette": "DEFAULT",
262 "palette_size": 10,
263 "custom_colors": [],
264 "color_axis": "CLASS",
265 "text": "Class",
266 "text_position": "TOP_LEFT",
267 "text_color": "WHITE",
268 "text_scale": 1,
269 "text_thickness": 1,
270 "text_padding": 10,
271 "border_radius": 0
272 }
273 ],
274 "outputs": [
275 {
276 "type": "JsonField",
277 "name": "general_object_detection_1_1",
278 "coordinates_system": "own",
279 "selector": "$steps.general_object_detection_1.predictions"
280 },
281 {
282 "type": "JsonField",
283 "name": "event_saver_1_1",
284 "coordinates_system": "own",
285 "selector": "$steps.event_saver_1.error_status"
286 },
287 {
288 "type": "JsonField",
289 "name": "event_saver_1_2",
290 "coordinates_system": "own",
291 "selector": "$steps.event_saver_1.throttling_status"
292 },
293 {
294 "type": "JsonField",
295 "name": "event_saver_1_3",
296 "coordinates_system": "own",
297 "selector": "$steps.event_saver_1.message"
298 },
299 {
300 "type": "JsonField",
301 "name": "event_saver_1_4",
302 "coordinates_system": "own",
303 "selector": "$steps.event_saver_1.image_url"
304 },
305 {
306 "type": "JsonField",
307 "name": "event_saver_1_5",
308 "coordinates_system": "own",
309 "selector": "$steps.event_saver_1.video_url"
310 },
311 {
312 "type": "JsonField",
313 "name": "detections_filter_1_1",
314 "coordinates_system": "own",
315 "selector": "$steps.detections_filter_1.predictions"
316 },
317 {
318 "type": "JsonField",
319 "name": "bounding_box_visualization_1_1",
320 "coordinates_system": "own",
321 "selector": "$steps.bounding_box_visualization_1.image"
322 },
323 {
324 "type": "JsonField",
325 "name": "detections_filter_2_1",
326 "coordinates_system": "own",
327 "selector": "$steps.detections_filter_2.predictions"
328 },
329 {
330 "type": "JsonField",
331 "name": "label_visualization_1_1",
332 "coordinates_system": "own",
333 "selector": "$steps.label_visualization_1.image"
334 }
335 ]
336 }
337 }
灭火器存在检测
用途：检测特定区域是否存在灭火器；可用于发现灭火器缺失或被挪走。
- 组成与流程：
目标检测：检测灭火器；
目标跟踪与可视化：绘制框与标签；
越界/在区时长：统计灭火器离开区域的时间并聚合；
条件继续：当离区时长达到阈值（示例 3s）进入事件保存；
事件保存与仪表盘：保存图片/视频并在仪表盘展示。
查看工作流 JSON
1{
2 "name": "灭火器存在检测",
3 "category": "Construction Site",
4 "notes": {
5 "notes_cn": "使用通用目标检测模型检测图片特定区域中是否存在灭火器，需要用户自行配置区域坐标。",
6 "notes_en": "Use the general detection model to detect whether there is a fire extinguisher in the specific area of the image, need to configure the region coordinates by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "core/bounding_box_visualization@v1",
19 "name": "bounding_box_visualization_1",
20 "comments": null,
21 "image": "$inputs.image",
22 "copy_image": true,
23 "predictions": "$steps.highway_tracker_1.tracked_detections",
24 "color_palette": "DEFAULT",
25 "palette_size": 10,
26 "custom_colors": [],
27 "color_axis": "CLASS",
28 "thickness": 2,
29 "roundness": 0
30 },
31 {
32 "type": "daoai/general_obj_det@v1",
33 "name": "general_object_detection_1",
34 "comments": null,
35 "images": "$inputs.image",
36 "classes": [
37 "fire extinguisher"
38 ],
39 "confidence_threshold": 0.5,
40 "label_confidence_thresholds": null,
41 "max_detections": 100
42 },
43 {
44 "type": "core/label_visualization@v1",
45 "name": "label_visualization_1",
46 "comments": null,
47 "image": "$steps.bounding_box_visualization_1.image",
48 "copy_image": true,
49 "predictions": "$steps.highway_tracker_1.tracked_detections",
50 "color_palette": "DEFAULT",
51 "palette_size": 10,
52 "custom_colors": [],
53 "color_axis": "CLASS",
54 "text": "Class",
55 "text_position": "TOP_LEFT",
56 "text_color": "WHITE",
57 "text_scale": 1,
58 "text_thickness": 1,
59 "text_padding": 10,
60 "border_radius": 0
61 },
62 {
63 "type": "daoai/time_out_zone@v1",
64 "name": "time_out_of_zone_1",
65 "comments": null,
66 "image": "$inputs.image",
67 "detections": "$steps.highway_tracker_1.tracked_detections",
68 "zone": [],
69 "triggering_anchor": "CENTER",
70 "remove_in_zone_detections": true
71 },
72 {
73 "type": "core/property_definition@v1",
74 "name": "property_definition_1",
75 "comments": null,
76 "data": "$steps.time_out_of_zone_1.timed_detections",
77 "operations": [
78 {
79 "type": "DetectionsPropertyExtract",
80 "property_name": "time_out_of_zone"
81 },
82 {
83 "type": "NumericSequenceAggregate",
84 "function": "max"
85 }
86 ],
87 "image": "$inputs.image"
88 },
89 {
90 "type": "core/continue_if@v1",
91 "name": "continue_if_1",
92 "comments": null,
93 "condition_statement": {
94 "type": "StatementGroup",
95 "statements": [
96 {
97 "type": "BinaryStatement",
98 "left_operand": {
99 "type": "DynamicOperand",
100 "operand_name": "left"
101 },
102 "comparator": {
103 "type": "(Number) >="
104 },
105 "right_operand": {
106 "type": "StaticOperand",
107 "value": 3
108 }
109 }
110 ],
111 "operator": "and",
112 "uistate": {
113 "leftOperand": "$steps.property_definition_1.output",
114 "detectionsEvaluationProperty": "value",
115 "selectedFilterType": "not_selected",
116 "isClassFilteringActive": false,
117 "isAttrFilteringActive": false,
118 "isConfidenceFilteringActive": false,
119 "classSetInclusionMode": "include",
120 "classList": [],
121 "attrList": [],
122 "attrSetInclusionMode": "include",
123 "confidenceThreshold": 0.5,
124 "confidenceOperator": ">=",
125 "referenceImage": null,
126 "sizeThreshold": 5,
127 "sizeThresholdOperator": "<=",
128 "zoneOperator": "in",
129 "zonePoints": [],
130 "detectionReferencePoint": "center",
131 "isZoneStatic": true,
132 "dynamicZone": null,
133 "runtimeParameter": null,
134 "parentClassName": "",
135 "confidenceAggregationMode": "max",
136 "confidenceAggregationOperator": ">=",
137 "confidenceAggregationThreshold": 0.5,
138 "comparator": "(Number) ==",
139 "comparisonType": "Statically",
140 "comparisonValue": "0",
141 "detectionsNumberOperator": "(Number) >=",
142 "detectionsNumberThreshold": 1,
143 "extractedImageProperty": "height",
144 "propertyValueOperator": ">=",
145 "referenceValue": 1,
146 "isReferenceValueStatic": true,
147 "nonImageInputOperation": "(Number) ==",
148 "isMultiLabel": false,
149 "multiLabelOperation": "==",
150 "isFilteringEnabled": false
151 }
152 },
153 "evaluation_parameters": {
154 "left": "$steps.property_definition_1.output"
155 },
156 "next_steps": [
157 "$steps.event_saver_1"
158 ],
159 "image": "$inputs.image"
160 },
161 {
162 "type": "daoai/event_saver@v1",
163 "name": "event_saver_1",
164 "comments": null,
165 "event_type": "Fire Extinguisher Lost",
166 "image": "$steps.label_visualization_1.image",
167 "original_image": "$inputs.image",
168 "save_video": true,
169 "video_length_seconds": 30,
170 "cooldown_seconds": 20,
171 "cooldown_session_key": null,
172 "per_type_cooldown_seconds": 30
173 },
174 {
175 "type": "daoai/dashboard_visualization@v1",
176 "name": "dashboard_visualization_1",
177 "comments": null,
178 "image": "$steps.label_visualization_1.image"
179 },
180 {
181 "type": "daoai/highway_tracker@v1",
182 "name": "highway_tracker_1",
183 "comments": null,
184 "image": "$inputs.image",
185 "detections": "$steps.general_object_detection_1.predictions",
186 "track_activation_threshold": 0.25,
187 "lost_track_buffer": 15,
188 "minimum_matching_threshold": 0.7,
189 "minimum_consecutive_frames": 1,
190 "instances_cache_size": 16384
191 }
192 ],
193 "outputs": [
194 {
195 "type": "JsonField",
196 "name": "bounding_box_visualization_1_1",
197 "coordinates_system": "own",
198 "selector": "$steps.bounding_box_visualization_1.image"
199 },
200 {
201 "type": "JsonField",
202 "name": "general_object_detection_1_1",
203 "coordinates_system": "own",
204 "selector": "$steps.general_object_detection_1.predictions"
205 },
206 {
207 "type": "JsonField",
208 "name": "label_visualization_1_1",
209 "coordinates_system": "own",
210 "selector": "$steps.label_visualization_1.image"
211 },
212 {
213 "type": "JsonField",
214 "name": "time_out_of_zone_1_1",
215 "coordinates_system": "own",
216 "selector": "$steps.time_out_of_zone_1.timed_detections"
217 },
218 {
219 "type": "JsonField",
220 "name": "property_definition_1_1",
221 "coordinates_system": "own",
222 "selector": "$steps.property_definition_1.output"
223 },
224 {
225 "type": "JsonField",
226 "name": "event_saver_1_1",
227 "coordinates_system": "own",
228 "selector": "$steps.event_saver_1.error_status"
229 },
230 {
231 "type": "JsonField",
232 "name": "event_saver_1_2",
233 "coordinates_system": "own",
234 "selector": "$steps.event_saver_1.throttling_status"
235 },
236 {
237 "type": "JsonField",
238 "name": "event_saver_1_3",
239 "coordinates_system": "own",
240 "selector": "$steps.event_saver_1.message"
241 },
242 {
243 "type": "JsonField",
244 "name": "event_saver_1_4",
245 "coordinates_system": "own",
246 "selector": "$steps.event_saver_1.image_url"
247 },
248 {
249 "type": "JsonField",
250 "name": "event_saver_1_5",
251 "coordinates_system": "own",
252 "selector": "$steps.event_saver_1.video_url"
253 },
254 {
255 "type": "JsonField",
256 "name": "highway_tracker_1_1",
257 "coordinates_system": "own",
258 "selector": "$steps.highway_tracker_1.tracked_detections"
259 },
260 {
261 "type": "JsonField",
262 "name": "highway_tracker_1_2",
263 "coordinates_system": "own",
264 "selector": "$steps.highway_tracker_1.new_instances"
265 },
266 {
267 "type": "JsonField",
268 "name": "highway_tracker_1_3",
269 "coordinates_system": "own",
270 "selector": "$steps.highway_tracker_1.already_seen_instances"
271 }
272 ]
273 }
274 }
通用
发送HTTP消息
用途：当检测到目标（示例：人员）时，触发自定义 Python 生成消息并通过 Webhook 推送到外部系统。
- 组成与流程：
目标检测：检测人员；
条件继续：当检测数量 >= 1 时，进入后续步骤；
自定义模块：生成文本消息；
查看工作流 JSON
1{
2 "name": "外部消息触发",
3 "category": "Any Scene",
4 "notes": {
5 "notes_cn": "使用 custom python 和 webhook sink 将检测结果实时推送至外部系统，实现平台联动与事件通知，需要用户自行配置 url。",
6 "notes_en": "Use custom python and webhook sink to push the detection results to the external system in real time, achieving platform linkage and event notification, need to configure the url by yourself."
7 },
8 "definition":{
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/general_detection_model@v1",
19 "name": "general_detection_model_fast_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "classes": [
23 "person"
24 ],
25 "confidence_threshold": null,
26 "label_confidence_thresholds": null,
27 "precision": "fp32",
28 "image_size": "640"
29 },
30 {
31 "type": "core/continue_if@v1",
32 "name": "continue_if_1",
33 "comments": null,
34 "condition_statement": {
35 "type": "StatementGroup",
36 "statements": [
37 {
38 "type": "BinaryStatement",
39 "left_operand": {
40 "type": "DynamicOperand",
41 "operand_name": "left",
42 "operations": [
43 {
44 "type": "SequenceLength"
45 }
46 ]
47 },
48 "comparator": {
49 "type": "(Number) >="
50 },
51 "right_operand": {
52 "type": "StaticOperand",
53 "value": 1
54 }
55 }
56 ],
57 "operator": "and",
58 "uistate": {
59 "leftOperand": "$steps.general_detection_model_fast_1.predictions",
60 "detectionsEvaluationProperty": "detection_count",
61 "selectedFilterType": "not_selected",
62 "isClassFilteringActive": false,
63 "isAttrFilteringActive": false,
64 "isConfidenceFilteringActive": false,
65 "classSetInclusionMode": "include",
66 "classList": [],
67 "attrList": [],
68 "attrSetInclusionMode": "include",
69 "confidenceThreshold": 0.5,
70 "confidenceOperator": ">=",
71 "referenceImage": null,
72 "sizeThreshold": 5,
73 "sizeThresholdOperator": "<=",
74 "zoneOperator": "in",
75 "zonePoints": [],
76 "detectionReferencePoint": "center",
77 "isZoneStatic": true,
78 "dynamicZone": null,
79 "runtimeParameter": null,
80 "parentClassName": "",
81 "confidenceAggregationMode": "max",
82 "confidenceAggregationOperator": ">=",
83 "confidenceAggregationThreshold": 0.5,
84 "comparator": "(Number) ==",
85 "comparisonType": "Statically",
86 "comparisonValue": "0",
87 "detectionsNumberOperator": "(Number) >=",
88 "detectionsNumberThreshold": 1,
89 "extractedImageProperty": "height",
90 "propertyValueOperator": ">=",
91 "referenceValue": 1,
92 "isReferenceValueStatic": true,
93 "nonImageInputOperation": "(Number) ==",
94 "isMultiLabel": false,
95 "multiLabelOperation": "==",
96 "isFilteringEnabled": false
97 }
98 },
99 "evaluation_parameters": {
100 "left": "$steps.general_detection_model_fast_1.predictions"
101 },
102 "next_steps": [
103 "$steps.Warning",
104 "$steps.webhook_sink_1"
105 ],
106 "image": "$inputs.image"
107 },
108 {
109 "type": "Warning",
110 "name": "Warning",
111 "img": "$inputs.image"
112 },
113 {
114 "type": "core/webhook_sink@v1",
115 "name": "webhook_sink_1",
116 "comments": null,
117 "url": "",
118 "method": "POST",
119 "headers": {
120 "Content-Type": "application/json; charset=utf-8"
121 },
122 "json_payload": {
123 "text": "$steps.Warning.msg"
124 },
125 "json_payload_operations": {},
126 "request_timeout": 2,
127 "fire_and_forget": true,
128 "disable_sink": false,
129 "cooldown_seconds": 5,
130 "image": "$inputs.image"
131 }
132 ],
133 "outputs": [
134 {
135 "type": "JsonField",
136 "name": "general_detection_model_fast_1_1",
137 "coordinates_system": "own",
138 "selector": "$steps.general_detection_model_fast_1.predictions"
139 },
140 {
141 "type": "JsonField",
142 "name": "msg",
143 "coordinates_system": "own",
144 "selector": "$steps.Warning.msg"
145 },
146 {
147 "type": "JsonField",
148 "name": "webhook_sink_1_1",
149 "coordinates_system": "own",
150 "selector": "$steps.webhook_sink_1.error_status"
151 },
152 {
153 "type": "JsonField",
154 "name": "webhook_sink_1_2",
155 "coordinates_system": "own",
156 "selector": "$steps.webhook_sink_1.throttling_status"
157 },
158 {
159 "type": "JsonField",
160 "name": "webhook_sink_1_3",
161 "coordinates_system": "own",
162 "selector": "$steps.webhook_sink_1.message"
163 }
164 ],
165 "dynamic_blocks_definitions": [
166 {
167 "type": "DynamicBlockDefinition",
168 "manifest": {
169 "type": "ManifestDescription",
170 "description": "",
171 "block_type": "Warning",
172 "inputs": {
173 "img": {
174 "type": "DynamicInputDefinition",
175 "selector_types": [
176 "input_image",
177 "step_output_image"
178 ],
179 "selector_data_kind": {
180 "input_image": [
181 "image"
182 ],
183 "step_output_image": [
184 "image"
185 ]
186 }
187 }
188 },
189 "outputs": {
190 "msg": {
191 "type": "DynamicOutputDefinition",
192 "kind": [
193 "string"
194 ]
195 }
196 }
197 },
198 "code": {
199 "type": "PythonCode",
200 "run_function_code": "def run(self, img) -> BlockResult:\n # Todo: write your code here\n return {\"msg\": \"Pedestrian Detected\"}"
201 }
202 }
203 ]
204 }
205}
数据采集与标注
用途：检测目标并将统计结果通过 HTTP 协议发送到外部服务。 组成与流程：
目标检测：检测目标类别（car）。
自定义模块：发送 HTTP 请求，载荷包含 "number_of_cars_detected" 统计结果；
可视化：绘制检测框用于结果展示；
查看工作流 JSON
1{
2 "version": "1.0",
3 "inputs": [
4 {
5 "type": "WorkflowImage",
6 "name": "image"
7 }
8 ],
9 "steps": [
10 {
11 "type": "daoai/general_obj_det@v1",
12 "name": "general_object_detection_1",
13 "comments": null,
14 "images": "$inputs.image",
15 "classes": [
16 "car"
17 ],
18 "confidence_threshold": null,
19 "label_confidence_thresholds": null,
20 "max_detections": 100
21 },
22 {
23 "type": "Send_Http_Request",
24 "name": "Send Http Request",
25 "input_url": "http://206.12.6.247:9000",
26 "prediction": "$steps.general_object_detection_1.predictions"
27 },
28 {
29 "type": "core/bounding_box_visualization@v1",
30 "name": "bounding_box_visualization_1",
31 "comments": null,
32 "image": "$inputs.image",
33 "copy_image": true,
34 "predictions": "$steps.general_object_detection_1.predictions",
35 "color_palette": "DEFAULT",
36 "palette_size": 10,
37 "custom_colors": [],
38 "color_axis": "CLASS",
39 "thickness": 2,
40 "roundness": 0
41 }
42 ],
43 "outputs": [
44 {
45 "type": "JsonField",
46 "name": "general_object_detection_1_1",
47 "coordinates_system": "own",
48 "selector": "$steps.general_object_detection_1.predictions"
49 },
50 {
51 "type": "JsonField",
52 "name": "status_code",
53 "coordinates_system": "own",
54 "selector": "$steps.Send Http Request.status_code"
55 },
56 {
57 "type": "JsonField",
58 "name": "message",
59 "coordinates_system": "own",
60 "selector": "$steps.Send Http Request.message"
61 },
62 {
63 "type": "JsonField",
64 "name": "bounding_box_visualization_1_1",
65 "coordinates_system": "own",
66 "selector": "$steps.bounding_box_visualization_1.image"
67 }
68 ],
69 "dynamic_blocks_definitions": [
70 {
71 "type": "DynamicBlockDefinition",
72 "manifest": {
73 "type": "ManifestDescription",
74 "description": "sends http request to 3rd party service",
75 "block_type": "Send_Http_Request",
76 "inputs": {
77 "input_url": {
78 "type": "DynamicInputDefinition",
79 "selector_types": [
80 "input_parameter",
81 "step_output"
82 ],
83 "selector_data_kind": {
84 "input_parameter": [
85 "string"
86 ],
87 "step_output": [
88 "string"
89 ]
90 },
91 "value_types": [
92 "string"
93 ]
94 },
95 "prediction": {
96 "type": "DynamicInputDefinition",
97 "selector_types": [
98 "input_parameter",
99 "step_output"
100 ],
101 "selector_data_kind": {
102 "input_parameter": [
103 "object_detection_prediction"
104 ],
105 "step_output": [
106 "object_detection_prediction"
107 ]
108 }
109 }
110 },
111 "outputs": {
112 "status_code": {
113 "type": "DynamicOutputDefinition",
114 "kind": [
115 "integer"
116 ]
117 },
118 "message": {
119 "type": "DynamicOutputDefinition",
120 "kind": [
121 "string"
122 ]
123 }
124 }
125 },
126 "code": {
127 "type": "PythonCode",
128 "run_function_code": "import requests\nimport numpy as np\n\ndef run(self, input_url, prediction) -> BlockResult:\n url = input_url\n\n car_number = int(np.sum(prediction.data['class_name'] == \"car\"))\n payload = {\n \"number_of_cars_detected\": car_number\n }\n\n try:\n response = requests.post(\n url=url,\n json=payload,\n timeout=5\n )\n\n return {\n \"status_code\": response.status_code,\n \"message\": response.text\n }\n\n except Exception as e:\n return {\n \"status_code\": -1,\n \"message\": str(e)\n }\n"
129 }
130 }
131 ]
132}
多模型逻辑检测
用途：并行/串行运行多模型，通过与/或逻辑组合实现复杂条件判定和结果融合（需替换具体模型 UID）。
- 组成与流程：
检测模型 A：初始目标检测；
条件筛选 + 动态裁剪：对指定目标生成裁剪区域；
分类模型 B/C：对裁剪图进行分类；
类别替换与融合：将检测与分类结果融合，替换类别并组合为最终输出；
可视化：叠加框与标签用于展示。
查看工作流 JSON
1{
2 "name": "多模型逻辑检测",
3 "category": "Uncertain",
4 "notes": {
5 "notes_cn": "支持多模型并行执行或串行执行，通过与 / 或逻辑组合，实现复杂条件判断与多层级结果输出，需要用户自行替换模型。",
6 "notes_en": "Support parallel execution or serial execution of multiple models, through AND / OR logic combinations, to achieve complex condition judgment and multi-level result output, need to configure the model by yourself."
7 },
8 "definition": {
9 "version": "1.0",
10 "inputs": [
11 {
12 "type": "WorkflowImage",
13 "name": "image"
14 }
15 ],
16 "steps": [
17 {
18 "type": "daoai/daoai_world_model@v1",
19 "name": "daoai_world_model_1",
20 "comments": null,
21 "images": "$inputs.image",
22 "model_type": "detection",
23 "model_uid": "CcaHeNg6gLrjg1rFqtA_EA",
24 "confidence_threshold": null,
25 "label_confidence_thresholds": null
26 },
27 {
28 "type": "core/detections_filter@v1",
29 "name": "detections_filter_1",
30 "comments": null,
31 "predictions": "$steps.general_object_detection_1.predictions",
32 "operations": [
33 {
34 "type": "DetectionsFilter",
35 "filter_operation": {
36 "type": "StatementGroup",
37 "statements": [
38 {
39 "type": "BinaryStatement",
40 "left_operand": {
41 "type": "DynamicOperand",
42 "operations": [
43 {
44 "type": "ExtractDetectionProperty",
45 "property_name": "class_name"
46 }
47 ]
48 },
49 "comparator": {
50 "type": "in (Sequence)"
51 },
52 "right_operand": {
53 "type": "StaticOperand",
54 "value": [
55 "car"
56 ]
57 }
58 }
59 ]
60 }
61 }
62 ],
63 "image": "$inputs.image",
64 "uistate": {
65 "operations": {
66 "filterBy": "class_confidence",
67 "parentClassName": "",
68 "objectClassEnabled": true,
69 "objectClassType": "include",
70 "objectClasses": "car",
71 "attributeEnabled": false,
72 "attributeType": "include",
73 "attributes": "",
74 "confidenceEnabled": false,
75 "confidenceOperator": ">=",
76 "confidenceValue": 0.5,
77 "imageInput": "$inputs.image",
78 "detectionSizeOperator": "<=",
79 "detectionSizeValue": 5,
80 "detectionLocation": "in",
81 "detectionReferencePoint": "center",
82 "zoneDefinition": "Define in Editor",
83 "zonePoints": [],
84 "zoneJson": "[]"
85 }
86 }
87 },
88 {
89 "type": "core/continue_if@v1",
90 "name": "continue_if_1",
91 "comments": null,
92 "condition_statement": {
93 "type": "StatementGroup",
94 "statements": [
95 {
96 "type": "BinaryStatement",
97 "left_operand": {
98 "type": "DynamicOperand",
99 "operand_name": "left",
100 "operations": [
101 {
102 "type": "SequenceLength"
103 }
104 ]
105 },
106 "comparator": {
107 "type": "(Number) >="
108 },
109 "right_operand": {
110 "type": "StaticOperand",
111 "value": 1
112 }
113 }
114 ],
115 "operator": "and",
116 "uistate": {
117 "leftOperand": "$steps.detections_filter_1.predictions",
118 "detectionsEvaluationProperty": "detection_count",
119 "selectedFilterType": "not_selected",
120 "isClassFilteringActive": false,
121 "isAttrFilteringActive": false,
122 "isConfidenceFilteringActive": false,
123 "classSetInclusionMode": "include",
124 "classList": [],
125 "attrList": [],
126 "attrSetInclusionMode": "include",
127 "confidenceThreshold": 0.5,
128 "confidenceOperator": ">=",
129 "referenceImage": null,
130 "sizeThreshold": 5,
131 "sizeThresholdOperator": "<=",
132 "zoneOperator": "in",
133 "zonePoints": [],
134 "detectionReferencePoint": "center",
135 "isZoneStatic": true,
136 "dynamicZone": null,
137 "runtimeParameter": null,
138 "parentClassName": "",
139 "confidenceAggregationMode": "max",
140 "confidenceAggregationOperator": ">=",
141 "confidenceAggregationThreshold": 0.5,
142 "comparator": "(Number) ==",
143 "comparisonType": "Statically",
144 "comparisonValue": "0",
145 "detectionsNumberOperator": "(Number) >=",
146 "detectionsNumberThreshold": 1,
147 "extractedImageProperty": "height",
148 "propertyValueOperator": ">=",
149 "referenceValue": 1,
150 "isReferenceValueStatic": true,
151 "nonImageInputOperation": "(Number) ==",
152 "isMultiLabel": false,
153 "multiLabelOperation": "==",
154 "isFilteringEnabled": false
155 }
156 },
157 "evaluation_parameters": {
158 "left": "$steps.detections_filter_1.predictions"
159 },
160 "next_steps": [
161 "$steps.dynamic_crop_1"
162 ],
163 "image": "$inputs.image"
164 },
165 {
166 "type": "core/dynamic_crop@v1",
167 "name": "dynamic_crop_1",
168 "comments": null,
169 "images": "$inputs.image",
170 "predictions": "$steps.detections_filter_1.predictions",
171 "mask_opacity": 0,
172 "background_color": [
173 0,
174 0,
175 0
176 ],
177 "image": "$inputs.image"
178 },
179 {
180 "type": "daoai/daoai_world_model@v1",
181 "name": "daoai_world_model_2",
182 "comments": null,
183 "images": "$steps.dynamic_crop_1.crops",
184 "model_type": "classification",
185 "model_uid": "1P70R27Ubofnbh0D0sHWxA",
186 "confidence_threshold": null,
187 "label_confidence_thresholds": null,
188 "image": "$inputs.image"
189 },
190 {
191 "type": "core/detections_filter@v1",
192 "name": "detections_filter_2",
193 "comments": null,
194 "predictions": "$steps.general_object_detection_1.predictions",
195 "operations": [
196 {
197 "type": "DetectionsFilter",
198 "filter_operation": {
199 "type": "StatementGroup",
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