mp4 for tracking
Browse files
main.py
CHANGED
@@ -63,9 +63,11 @@ def show_tracking(video_content, vis_out_dir, model):
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# Go through frames and write them
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for frame_track in video_track:
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result_track = frame_track[0].plot() # plot a BGR numpy array of predictions
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print("[INFO] Done with frames")
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#print(type(result_pose)) numpy ndarray
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-
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out_track.release()
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@@ -110,17 +112,17 @@ def infer(video, check):
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out_files.extend(out_file)
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print(out_files)
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-
return out_files[0], out_files[1], out_files[2]
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def run():
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#https://github.com/open-mmlab/mmpose/blob/main/docs/en/user_guides/inference.md
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-
check_web = gr.CheckboxGroup(choices = ["Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"
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-
check_file = gr.CheckboxGroup(choices = ["Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"
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webcam = gr.Interface(
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fn=infer,
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inputs= [gr.Video(source="webcam", height=412), check_web],
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outputs = [gr.
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title = 'Pose estimation',
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description = 'Pose estimation on video',
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allow_flagging=False
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@@ -129,7 +131,7 @@ def run():
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file = gr.Interface(
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infer,
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inputs = [gr.Video(source="upload", height=412), check_file],
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-
outputs = [gr.
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allow_flagging=False
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)
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# Go through frames and write them
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for frame_track in video_track:
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result_track = frame_track[0].plot() # plot a BGR numpy array of predictions
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+
out_track.write(result_track)
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+
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print("[INFO] Done with frames")
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#print(type(result_pose)) numpy ndarray
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+
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out_track.release()
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out_files.extend(out_file)
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print(out_files)
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+
return "track.mp4", out_files[0], out_files[1], out_files[2] # out_files[3]
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def run():
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#https://github.com/open-mmlab/mmpose/blob/main/docs/en/user_guides/inference.md
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+
check_web = gr.CheckboxGroup(choices = ["Detect and track", "Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"], label="Methods", type="value", info="Select the model(s) you want")
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+
check_file = gr.CheckboxGroup(choices = ["Detect and track", "Estimate human 2d poses", "Estimate human 2d hand poses", "Estimate human 3d poses"], label="Methods", type="value", info="Select the model(s) you want")
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webcam = gr.Interface(
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fn=infer,
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inputs= [gr.Video(source="webcam", height=412), check_web],
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+
outputs = [gr.Video(format='mp4'), gr.PlayableVideo(), gr.PlayableVideo(), gr.PlayableVideo()],
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title = 'Pose estimation',
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description = 'Pose estimation on video',
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allow_flagging=False
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file = gr.Interface(
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infer,
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inputs = [gr.Video(source="upload", height=412), check_file],
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outputs = [gr.Video(format='mp4'), gr.PlayableVideo(), gr.PlayableVideo(), gr.PlayableVideo()],
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allow_flagging=False
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)
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