Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
7a2c317
1
Parent(s):
c34b80e
fix error when no person detected in video
Browse files
app.py
CHANGED
@@ -155,7 +155,6 @@ def process_video(
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# ------------------------------------------------------------------------
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# Stage 1. Detect humans on the image
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# ------------------------------------------------------------------------
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-
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inputs = person_image_processor(images=frame, return_tensors="pt").to(
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device
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)
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@@ -182,6 +181,9 @@ def process_video(
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# Stage 2. Detect keypoints for each person found
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# ------------------------------------------------------------------------
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inputs = image_processor(
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frame, boxes=[person_boxes], return_tensors="pt"
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).to(device)
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@@ -231,7 +233,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
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gr.Markdown(
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"""
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SynthPose is a new approach that enables finetuning of pre-trained 2D human pose models to predict an arbitrarily denser set of keypoints for accurate kinematic analysis through the use of synthetic data.
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-
More details are available in [OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics](https://arxiv.org/abs/2406.09788)
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This particular variant was finetuned on a set of keypoints usually found on motion capture setups, and include coco keypoints as well.<br />
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The keypoints part of the skeleton are the COCO keypoints, and the pink ones the anatomical markers.
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"""
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# ------------------------------------------------------------------------
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# Stage 1. Detect humans on the image
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# ------------------------------------------------------------------------
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inputs = person_image_processor(images=frame, return_tensors="pt").to(
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device
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)
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# Stage 2. Detect keypoints for each person found
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# ------------------------------------------------------------------------
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+
if len(person_boxes) == 0:
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+
sink.write_frame(frame)
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+
continue
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inputs = image_processor(
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frame, boxes=[person_boxes], return_tensors="pt"
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).to(device)
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gr.Markdown(
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"""
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SynthPose is a new approach that enables finetuning of pre-trained 2D human pose models to predict an arbitrarily denser set of keypoints for accurate kinematic analysis through the use of synthetic data.
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+
More details are available in [OpenCapBench: A Benchmark to Bridge Pose Estimation and Biomechanics](https://arxiv.org/abs/2406.09788).<br />
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This particular variant was finetuned on a set of keypoints usually found on motion capture setups, and include coco keypoints as well.<br />
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The keypoints part of the skeleton are the COCO keypoints, and the pink ones the anatomical markers.
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"""
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