Changes
On November 8, 2023 at 3:29:45 PM UTC, Marija Knezevic:
-
Updated description of Traffic Camera Tracking (SAVeNoW) from
Main goals of this project is to detect, track and obtain velocity information of seven different traffic actors (Escooter, Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a video footage of a traffic intersection in Ingolstadt. This project is a part of SaveNoW, where all these data are used to create a digital twin of Ingolstadt for simulation purposes. <img src="https://raw.githubusercontent.com/savenow/Traffic_Camera_Tracking/main/readme_photos/Overview.png" alt="B3" width="800px"> <img src="https://github.com/savenow/Traffic_Camera_Tracking/blob/main/readme_photos/sample_inference.gif" alt="B3" width="800px"> This algorithm has been specially trained to distinguish between cyclists, e-scooter riders and pedestrians. This data is important to better study the traffic density and the behavior of e-scooters. The weights of the Network are currently not part of the Github repo. If you are interessted in the weights, please contact Pascal Brunner.
toMain goals of this project is to detect, track and obtain velocity information of seven different traffic actors (Escooter, Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a video footage of a traffic intersection in Ingolstadt. This project is a part of SaveNoW, where all these data are used to create a digital twin of Ingolstadt for simulation purposes. <img src="https://raw.githubusercontent.com/savenow/Traffic_Camera_Tracking/main/readme_photos/Overview.png" alt="B3" width="800px"> <img src="hhttps://github.com/savenow/Traffic_Camera_Tracking/blob/main/readme_photos/sample_inference.gif?raw=true" alt="B3" width="800px"> This algorithm has been specially trained to distinguish between cyclists, e-scooter riders and pedestrians. This data is important to better study the traffic density and the behavior of e-scooters. The weights of the Network are currently not part of the Github repo. If you are interessted in the weights, please contact Pascal Brunner.
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44 | "name": "traffic-camera-tracking-savenow", | 44 | "name": "traffic-camera-tracking-savenow", | ||
45 | "notes": "Main goals of this project is to detect, track and obtain | 45 | "notes": "Main goals of this project is to detect, track and obtain | ||
46 | velocity information of seven different traffic actors (Escooter, | 46 | velocity information of seven different traffic actors (Escooter, | ||
47 | Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a video | 47 | Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a video | ||
48 | footage of a traffic intersection in Ingolstadt. This project is a | 48 | footage of a traffic intersection in Ingolstadt. This project is a | ||
49 | part of SaveNoW, where all these data are used to create a digital | 49 | part of SaveNoW, where all these data are used to create a digital | ||
50 | twin of Ingolstadt for simulation purposes.\r\n\r\n<img | 50 | twin of Ingolstadt for simulation purposes.\r\n\r\n<img | ||
51 | .com/savenow/Traffic_Camera_Tracking/main/readme_photos/Overview.png\" | 51 | .com/savenow/Traffic_Camera_Tracking/main/readme_photos/Overview.png\" | ||
52 | alt=\"B3\" width=\"800px\">\r\n\r\n<img | 52 | alt=\"B3\" width=\"800px\">\r\n\r\n<img | ||
t | 53 | Traffic_Camera_Tracking/blob/main/readme_photos/sample_inference.gif\" | t | 53 | amera_Tracking/blob/main/readme_photos/sample_inference.gif?raw=true\" |
54 | alt=\"B3\" width=\"800px\">\r\n\r\nThis algorithm has been specially | 54 | alt=\"B3\" width=\"800px\">\r\n\r\nThis algorithm has been specially | ||
55 | trained to distinguish between cyclists, e-scooter riders and | 55 | trained to distinguish between cyclists, e-scooter riders and | ||
56 | pedestrians. This data is important to better study the traffic | 56 | pedestrians. This data is important to better study the traffic | ||
57 | density and the behavior of e-scooters. \r\nThe weights of the Network | 57 | density and the behavior of e-scooters. \r\nThe weights of the Network | ||
58 | are currently not part of the Github repo. If you are interessted in | 58 | are currently not part of the Github repo. If you are interessted in | ||
59 | the weights, please contact Pascal Brunner.", | 59 | the weights, please contact Pascal Brunner.", | ||
60 | "num_resources": 1, | 60 | "num_resources": 1, | ||
61 | "num_tags": 2, | 61 | "num_tags": 2, | ||
62 | "organization": { | 62 | "organization": { | ||
63 | "approval_status": "approved", | 63 | "approval_status": "approved", | ||
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68 | "is_organization": true, | 68 | "is_organization": true, | ||
69 | "name": "technische-hochschule-ingolstadt-thi", | 69 | "name": "technische-hochschule-ingolstadt-thi", | ||
70 | "state": "active", | 70 | "state": "active", | ||
71 | "title": "Technische Hochschule Ingolstadt (THI)", | 71 | "title": "Technische Hochschule Ingolstadt (THI)", | ||
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108 | "allowed_users": "", | 108 | "allowed_users": "", | ||
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111 | "created": "2023-10-24T12:12:13.729358", | 111 | "created": "2023-10-24T12:12:13.729358", | ||
112 | "datastore_active": false, | 112 | "datastore_active": false, | ||
113 | "description": "Main goals of this project is to detect, track | 113 | "description": "Main goals of this project is to detect, track | ||
114 | and obtain velocity information of seven different traffic actors | 114 | and obtain velocity information of seven different traffic actors | ||
115 | (Escooter, Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a | 115 | (Escooter, Pedestrians, Cyclists, Motorcycle, Car, Truck, Bus) from a | ||
116 | video footage of a traffic intersection in Ingolstadt. This project is | 116 | video footage of a traffic intersection in Ingolstadt. This project is | ||
117 | a part of SaveNoW, where all these data are used to create a digital | 117 | a part of SaveNoW, where all these data are used to create a digital | ||
118 | twin of Ingolstadt for simulation purposes.", | 118 | twin of Ingolstadt for simulation purposes.", | ||
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126 | "name": "Traffic Camera Tracking (SaveNow)", | 126 | "name": "Traffic Camera Tracking (SaveNow)", | ||
127 | "package_id": "44439bd2-1c77-439b-9393-0417429f79e6", | 127 | "package_id": "44439bd2-1c77-439b-9393-0417429f79e6", | ||
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132 | "state": "active", | 132 | "state": "active", | ||
133 | "url": | 133 | "url": | ||
134 | .com/savenow/Traffic_Camera_Tracking#traffic-camera-tracking-savenow", | 134 | .com/savenow/Traffic_Camera_Tracking#traffic-camera-tracking-savenow", | ||
135 | "url_type": null | 135 | "url_type": null | ||
136 | } | 136 | } | ||
137 | ], | 137 | ], | ||
138 | "spatial": | 138 | "spatial": | ||
139 | [11.426468,48.775905],[11.426468,48.774519],[11.42355,48.774519]]]]}", | 139 | [11.426468,48.775905],[11.426468,48.774519],[11.42355,48.774519]]]]}", | ||
140 | "state": "active", | 140 | "state": "active", | ||
141 | "tags": [ | 141 | "tags": [ | ||
142 | { | 142 | { | ||
143 | "display_name": "Object classification", | 143 | "display_name": "Object classification", | ||
144 | "id": "d2b5fcc8-19ae-47ed-9fb9-fd3faad2ada7", | 144 | "id": "d2b5fcc8-19ae-47ed-9fb9-fd3faad2ada7", | ||
145 | "name": "Object classification", | 145 | "name": "Object classification", | ||
146 | "state": "active", | 146 | "state": "active", | ||
147 | "vocabulary_id": null | 147 | "vocabulary_id": null | ||
148 | }, | 148 | }, | ||
149 | { | 149 | { | ||
150 | "display_name": "Object detection", | 150 | "display_name": "Object detection", | ||
151 | "id": "1082157c-a4bf-4436-adc8-53ccb83678bd", | 151 | "id": "1082157c-a4bf-4436-adc8-53ccb83678bd", | ||
152 | "name": "Object detection", | 152 | "name": "Object detection", | ||
153 | "state": "active", | 153 | "state": "active", | ||
154 | "vocabulary_id": null | 154 | "vocabulary_id": null | ||
155 | } | 155 | } | ||
156 | ], | 156 | ], | ||
157 | "title": "Traffic Camera Tracking (SAVeNoW)", | 157 | "title": "Traffic Camera Tracking (SAVeNoW)", | ||
158 | "type": "dataset", | 158 | "type": "dataset", | ||
159 | "url": null, | 159 | "url": null, | ||
160 | "version": "" | 160 | "version": "" | ||
161 | } | 161 | } |