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Browse files- README.md +24 -0
- app.py +122 -0
- pre-requirements.txt +2 -0
- requirements.txt +10 -0
- videos/apple.mp4 +0 -0
- videos/bear.mp4 +0 -0
- videos/paragliding-launch.mp4 +0 -0
- videos/paragliding.mp4 +0 -0
README.md
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---
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title: CoTracker
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emoji: 🎨
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colorFrom: yellow
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colorTo: pink
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sdk: gradio
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sdk_version: 3.41.2
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app_file: app.py
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pinned: false
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license: cc-by-nc-4.0
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---
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This is a demo for ["CoTracker: It is Better to Track Together"](https://arxiv.org/abs/2307.07635)
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```
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@misc{karaev2023cotracker,
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title={CoTracker: It is Better to Track Together},
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author={Nikita Karaev and Ignacio Rocco and Benjamin Graham and Natalia Neverova and Andrea Vedaldi and Christian Rupprecht},
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year={2023},
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eprint={2307.07635},
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archivePrefix={arXiv},
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primaryClass={cs.CV}
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}
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```
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app.py
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import os
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import cv2
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import imutils
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import torch
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import timm
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import einops
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import tqdm
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import numpy as np
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import gradio as gr
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from cotracker.utils.visualizer import Visualizer
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def parse_video(video_file):
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vs = cv2.VideoCapture(video_file)
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frames = []
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while True:
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(gotit, frame) = vs.read()
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if frame is not None:
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frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
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frames.append(frame)
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if not gotit:
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break
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return np.stack(frames)
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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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backward_tracking: bool = False,
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tracks_leave_trace: bool = False
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):
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load_video = parse_video(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", "cotracker_w8")
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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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pred_tracks, pred_visibility = model(
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load_video,
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grid_size=grid_size,
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grid_query_frame=grid_query_frame,
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backward_tracking=backward_tracking
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)
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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.cpu(),
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tracks=pred_tracks.cpu(),
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visibility=pred_visibility.cpu(),
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filename=filename,
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query_frame=grid_query_frame,
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)
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return os.path.join(
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os.path.dirname(__file__), "results", f"{filename}_pred_track.mp4"
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)
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apple = os.path.join(os.path.dirname(__file__), "videos", "apple.mp4")
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bear = os.path.join(os.path.dirname(__file__), "videos", "bear.mp4")
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paragliding_launch = os.path.join(os.path.dirname(__file__), "videos", "paragliding-launch.mp4")
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paragliding = os.path.join(os.path.dirname(__file__), "videos", "paragliding.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>Use <b>Backward Tracking</b> to track points from the selected frame in both directions.</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(type="file", 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, default=0, label="Grid Query Frame"),
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gr.Checkbox(label="Backward Tracking"),
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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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[ apple, 10, 0, False, False ],
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[ apple, 20, 30, True, False ],
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[ bear, 10, 0, False, False ],
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[ paragliding, 10, 0, False, False ],
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[ paragliding_launch, 10, 0, False, False ],
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],
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cache_examples=False,
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allow_flagging=False,
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)
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app.queue(max_size=20, concurrency_count=2).launch(debug=True)
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pre-requirements.txt
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torch==1.13.0
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torchvision==0.14.0
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requirements.txt
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@@ -0,0 +1,10 @@
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einops
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timm
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tqdm
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opencv-python
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matplotlib
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moviepy
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flow_vis
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imutils
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numpy
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git+https://github.com/facebookresearch/co-tracker.git
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videos/apple.mp4
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Binary file (726 kB). View file
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videos/bear.mp4
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videos/paragliding-launch.mp4
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Binary file (829 kB). View file
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videos/paragliding.mp4
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Binary file (438 kB). View file
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