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  1. app.ipynb +320 -8
  2. app.py +3 -8
app.ipynb CHANGED
@@ -18,7 +18,7 @@
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  "output_type": "stream",
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  "text": [
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  "Running on local URL: http://127.0.0.1:7860\n",
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- "Running on public URL: https://115f49f564465f60ec.gradio.live\n",
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  "\n",
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  "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
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  ]
@@ -26,7 +26,7 @@
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  {
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  "data": {
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  "text/html": [
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- "<div><iframe src=\"https://115f49f564465f60ec.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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  ],
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  "text/plain": [
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  "<IPython.core.display.HTML object>"
@@ -42,6 +42,324 @@
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  "execution_count": 1,
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  "metadata": {},
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  "output_type": "execute_result"
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  ],
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  "source": [
@@ -66,18 +384,12 @@
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  " gr.Markdown(\n",
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  " \"\"\"\n",
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  " # Vehicle detection using Yolo-v9\n",
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- " Upload the vehicle image or video for detection\n",
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  " \"\"\"\n",
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  " )\n",
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  "\n",
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  " with gr.Tab(\"Video\"):\n",
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  " gr.Markdown(\n",
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  " \"\"\"\n",
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- " Upload video mp4 file and detect the count of vehicles passing by\n",
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- " \"\"\"\n",
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- " )\n",
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- " gr.Markdown(\n",
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- " \"\"\"\n",
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  " Upload image file and detect vehicles present in the image\n",
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  " \"\"\"\n",
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  " )\n",
 
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  "output_type": "stream",
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  "text": [
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  "Running on local URL: http://127.0.0.1:7860\n",
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+ "Running on public URL: https://791bc0246f844ee823.gradio.live\n",
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  "\n",
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  "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
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  ]
 
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  {
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  "data": {
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  "text/html": [
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+ "<div><iframe src=\"https://791bc0246f844ee823.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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  ],
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  "text/plain": [
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  "<IPython.core.display.HTML object>"
 
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  "execution_count": 1,
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  "metadata": {},
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  "output_type": "execute_result"
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+ },
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+ {
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+ "name": "stderr",
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+ "output_type": "stream",
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+ "text": [
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+ "\u001b[34m\u001b[1mdetect: \u001b[0mweights=['yolov9/runs/train/exp/weights/best.pt'], source=/tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4, data=yolov9/data/coco128.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=cpu, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=yolov9/runs/detect, name=664a80cf-ce01-4bde-a090-59a93c91e364, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False, vid_stride=1\n",
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+ "YOLO 🚀 v0.1-89-g93f1a28 Python-3.10.14 torch-2.3.0+cu121 CPU\n",
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+ "\n",
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+ "Fusing layers... \n",
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+ "yolov9-e summary: 839 layers, 68555524 parameters, 0 gradients, 240.7 GFLOPs\n",
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+ "video 1/1 (1/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1617.8ms\n",
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+ "video 1/1 (2/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1498.3ms\n",
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+ "video 1/1 (3/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1423.7ms\n",
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+ "video 1/1 (4/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1210.8ms\n",
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+ "video 1/1 (5/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1229.1ms\n",
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+ "video 1/1 (6/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1 truck, 1367.8ms\n",
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+ "video 1/1 (7/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1 truck, 1486.9ms\n",
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276
+ "video 1/1 (222/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1329.8ms\n",
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+ "video 1/1 (223/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1346.3ms\n",
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+ "video 1/1 (224/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1348.2ms\n",
279
+ "video 1/1 (225/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1593.1ms\n",
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+ "video 1/1 (226/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1335.0ms\n",
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+ "video 1/1 (227/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1345.2ms\n",
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+ "video 1/1 (228/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1339.9ms\n",
283
+ "video 1/1 (229/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1397.7ms\n",
284
+ "video 1/1 (230/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1356.2ms\n",
285
+ "video 1/1 (231/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1390.5ms\n",
286
+ "video 1/1 (232/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1350.1ms\n",
287
+ "video 1/1 (233/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1365.0ms\n",
288
+ "video 1/1 (234/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1735.1ms\n",
289
+ "video 1/1 (235/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1445.3ms\n",
290
+ "video 1/1 (236/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1344.4ms\n",
291
+ "video 1/1 (237/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1340.4ms\n",
292
+ "video 1/1 (238/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1351.1ms\n",
293
+ "video 1/1 (239/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1346.8ms\n",
294
+ "video 1/1 (240/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1338.5ms\n",
295
+ "video 1/1 (241/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1387.6ms\n",
296
+ "video 1/1 (242/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1442.2ms\n",
297
+ "video 1/1 (243/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1325.5ms\n",
298
+ "video 1/1 (244/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1350.5ms\n",
299
+ "video 1/1 (245/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1361.8ms\n",
300
+ "video 1/1 (246/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1337.1ms\n",
301
+ "video 1/1 (247/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1344.6ms\n",
302
+ "video 1/1 (248/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1401.4ms\n",
303
+ "video 1/1 (249/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1337.2ms\n",
304
+ "video 1/1 (250/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1346.8ms\n",
305
+ "video 1/1 (251/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1356.8ms\n",
306
+ "video 1/1 (252/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1353.3ms\n",
307
+ "video 1/1 (253/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1363.3ms\n",
308
+ "video 1/1 (254/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1442.7ms\n",
309
+ "video 1/1 (255/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1453.3ms\n",
310
+ "video 1/1 (256/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1341.0ms\n",
311
+ "video 1/1 (257/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1325.8ms\n",
312
+ "video 1/1 (258/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1348.7ms\n",
313
+ "video 1/1 (259/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1628.3ms\n",
314
+ "video 1/1 (260/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1498.0ms\n",
315
+ "video 1/1 (261/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1980.8ms\n",
316
+ "video 1/1 (262/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1738.5ms\n",
317
+ "video 1/1 (263/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1351.8ms\n",
318
+ "video 1/1 (264/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 2 cars, 1439.5ms\n",
319
+ "video 1/1 (265/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1331.8ms\n",
320
+ "video 1/1 (266/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1734.1ms\n",
321
+ "video 1/1 (267/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1780.9ms\n",
322
+ "video 1/1 (268/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1848.5ms\n",
323
+ "video 1/1 (269/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1778.2ms\n",
324
+ "video 1/1 (270/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1787.7ms\n",
325
+ "video 1/1 (271/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1798.7ms\n",
326
+ "video 1/1 (272/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1712.4ms\n",
327
+ "video 1/1 (273/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1781.3ms\n",
328
+ "video 1/1 (274/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1341.2ms\n",
329
+ "video 1/1 (275/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1402.7ms\n",
330
+ "video 1/1 (276/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1360.8ms\n",
331
+ "video 1/1 (277/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1362.1ms\n",
332
+ "video 1/1 (278/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1370.1ms\n",
333
+ "video 1/1 (279/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1383.0ms\n",
334
+ "video 1/1 (280/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1418.8ms\n",
335
+ "video 1/1 (281/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1352.0ms\n",
336
+ "video 1/1 (282/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1361.7ms\n",
337
+ "video 1/1 (283/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1533.7ms\n",
338
+ "video 1/1 (284/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1333.1ms\n",
339
+ "video 1/1 (285/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1775.2ms\n",
340
+ "video 1/1 (286/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1817.8ms\n",
341
+ "video 1/1 (287/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1314.1ms\n",
342
+ "video 1/1 (288/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1349.4ms\n",
343
+ "video 1/1 (289/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1344.9ms\n",
344
+ "video 1/1 (290/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1337.2ms\n",
345
+ "video 1/1 (291/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1378.6ms\n",
346
+ "video 1/1 (292/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1397.3ms\n",
347
+ "video 1/1 (293/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1336.6ms\n",
348
+ "video 1/1 (294/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1348.8ms\n",
349
+ "video 1/1 (295/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1324.5ms\n",
350
+ "video 1/1 (296/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1377.5ms\n",
351
+ "video 1/1 (297/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1351.6ms\n",
352
+ "video 1/1 (298/298) /tmp/gradio/96ee097452acb133f511bd6cb20730ac92412476/cut_a_2.mp4: 416x640 1 car, 1357.3ms\n",
353
+ "Speed: 0.7ms pre-process, 1475.3ms inference, 1.4ms NMS per image at shape (1, 3, 640, 640)\n",
354
+ "Results saved to \u001b[1myolov9/runs/detect/664a80cf-ce01-4bde-a090-59a93c91e364\u001b[0m\n"
355
+ ]
356
+ },
357
+ {
358
+ "name": "stdout",
359
+ "output_type": "stream",
360
+ "text": [
361
+ "yolov9/runs/detect/664a80cf-ce01-4bde-a090-59a93c91e364/cut_a_2.mp4\n"
362
+ ]
363
  }
364
  ],
365
  "source": [
 
384
  " gr.Markdown(\n",
385
  " \"\"\"\n",
386
  " # Vehicle detection using Yolo-v9\n",
 
387
  " \"\"\"\n",
388
  " )\n",
389
  "\n",
390
  " with gr.Tab(\"Video\"):\n",
391
  " gr.Markdown(\n",
392
  " \"\"\"\n",
 
 
 
 
 
393
  " Upload image file and detect vehicles present in the image\n",
394
  " \"\"\"\n",
395
  " )\n",
app.py CHANGED
@@ -9,6 +9,7 @@ def inference(input_img):
9
  shell = f"python yolov9/detect.py --source {input_img} --img 640 --device cpu --weights yolov9/runs/train/exp/weights/best.pt --name {temp}"
10
  os.system(shell)
11
  return f"yolov9/runs/detect/{temp}/{input_img.split('/')[-1]}"
 
12
 
13
  def inference_video(input_img):
14
  org_img = input_img
@@ -18,24 +19,18 @@ with gr.Blocks() as demo:
18
  gr.Markdown(
19
  """
20
  # Vehicle detection using Yolo-v9
21
- Upload the vehicle image or video for detection
22
  """
23
  )
24
 
25
  with gr.Tab("Video"):
26
- gr.Markdown(
27
- """
28
- Upload video mp4 file and detect the count of vehicles passing by
29
- """
30
- )
31
  gr.Markdown(
32
  """
33
  Upload image file and detect vehicles present in the image
34
  """
35
  )
36
  with gr.Row():
37
- img_input = [gr.Video(label="Input Image",width=300, height=300)]
38
- pred_outputs = [gr.Video(label="Output Image",width=300, height=300)]
39
 
40
  image_button = gr.Button("Predict")
41
  image_button.click(inference, inputs=img_input, outputs=pred_outputs)
 
9
  shell = f"python yolov9/detect.py --source {input_img} --img 640 --device cpu --weights yolov9/runs/train/exp/weights/best.pt --name {temp}"
10
  os.system(shell)
11
  return f"yolov9/runs/detect/{temp}/{input_img.split('/')[-1]}"
12
+ #return "yolov9/runs/detect/f807164a-496b-413c-bb47-f5daf8803dcd/cut_a_1.mp4"
13
 
14
  def inference_video(input_img):
15
  org_img = input_img
 
19
  gr.Markdown(
20
  """
21
  # Vehicle detection using Yolo-v9
 
22
  """
23
  )
24
 
25
  with gr.Tab("Video"):
 
 
 
 
 
26
  gr.Markdown(
27
  """
28
  Upload image file and detect vehicles present in the image
29
  """
30
  )
31
  with gr.Row():
32
+ img_input = [gr.PlayableVideo(label="Input Image", autoplay=True, width=300, height=300)]
33
+ pred_outputs = [gr.PlayableVideo(label="Output Image",width=640, autoplay=True, height=640)]
34
 
35
  image_button = gr.Button("Predict")
36
  image_button.click(inference, inputs=img_input, outputs=pred_outputs)