90 lines
3.4 KiB
Python
90 lines
3.4 KiB
Python
import os
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import torch
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import gradio as gr
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from cotracker.utils.visualizer import Visualizer, read_video_from_path
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def cotracker_demo(
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input_video,
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grid_size: int = 10,
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grid_query_frame: int = 0,
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tracks_leave_trace: bool = False,
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):
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load_video = read_video_from_path(input_video)
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grid_query_frame = min(len(load_video) - 1, grid_query_frame)
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load_video = torch.from_numpy(load_video).permute(0, 3, 1, 2)[None].float()
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model = torch.hub.load("facebookresearch/co-tracker", "cotracker2_online")
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if torch.cuda.is_available():
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model = model.cuda()
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load_video = load_video.cuda()
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model(video_chunk=load_video, is_first_step=True, grid_size=grid_size)
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for ind in range(0, load_video.shape[1] - model.step, model.step):
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pred_tracks, pred_visibility = model(
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video_chunk=load_video[:, ind : ind + model.step * 2]
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) # B T N 2, B T N 1
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linewidth = 2
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if grid_size < 10:
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linewidth = 4
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elif grid_size < 20:
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linewidth = 3
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vis = Visualizer(
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save_dir=os.path.join(os.path.dirname(__file__), "results"),
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grayscale=False,
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pad_value=100,
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fps=10,
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linewidth=linewidth,
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show_first_frame=5,
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tracks_leave_trace=-1 if tracks_leave_trace else 0,
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)
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import time
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def current_milli_time():
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return round(time.time() * 1000)
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filename = str(current_milli_time())
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vis.visualize(
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load_video,
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tracks=pred_tracks,
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visibility=pred_visibility,
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filename=f"{filename}_pred_track",
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query_frame=grid_query_frame,
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)
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return os.path.join(os.path.dirname(__file__), "results", f"{filename}_pred_track.mp4")
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app = gr.Interface(
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title="🎨 CoTracker: It is Better to Track Together",
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description="<div style='text-align: left;'> \
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<p>Welcome to <a href='http://co-tracker.github.io' target='_blank'>CoTracker</a>! This space demonstrates point (pixel) tracking in videos. \
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Points are sampled on a regular grid and are tracked jointly. </p> \
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<p> To get started, simply upload your <b>.mp4</b> video in landscape orientation or click on one of the example videos to load them. The shorter the video, the faster the processing. We recommend submitting short videos of length <b>2-7 seconds</b>.</p> \
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<ul style='display: inline-block; text-align: left;'> \
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<li>The total number of grid points is the square of <b>Grid Size</b>.</li> \
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<li>To specify the starting frame for tracking, adjust <b>Grid Query Frame</b>. Tracks will be visualized only after the selected frame.</li> \
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<li>Check <b>Visualize Track Traces</b> to visualize traces of all the tracked points. </li> \
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</ul> \
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<p style='text-align: left'>For more details, check out our <a href='https://github.com/facebookresearch/co-tracker' target='_blank'>GitHub Repo</a> ⭐</p> \
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</div>",
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fn=cotracker_demo,
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inputs=[
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gr.Video(label="Input video", interactive=True),
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gr.Slider(minimum=1, maximum=30, step=1, value=10, label="Grid Size"),
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gr.Slider(minimum=0, maximum=30, step=1, value=0, label="Grid Query Frame"),
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gr.Checkbox(label="Visualize Track Traces"),
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],
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outputs=gr.Video(label="Video with predicted tracks"),
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examples=[
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["./assets/apple.mp4", 20, 0, False, False],
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["./assets/apple.mp4", 10, 30, True, False],
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],
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cache_examples=False,
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)
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app.launch(share=True)
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