Théo Rousseaux commited on
Commit
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1 Parent(s): 720638f

squat inference

Browse files
.gitattributes CHANGED
@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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  data/pose/squat.mp4 filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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  data/pose/squat.mp4 filter=lfs diff=lfs merge=lfs -text
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+ data/pose/squat_inference.mp4 filter=lfs diff=lfs merge=lfs -text
Modules/PoseEstimation/pose_estimation.ipynb ADDED
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 8,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "from ultralytics import YOLO\n",
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+ "\n",
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+ "# Load a model\n",
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+ "model = YOLO('yolov8n-pose.pt') # pretrained YOLOv8n model"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 9,
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "class PoseEstimator():\n",
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+ " def __init__(self):\n",
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+ " self.model = YOLO('yolov8n.pt')"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 10,
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "Downloading https://github.com/ultralytics/assets/releases/download/v8.2.0/yolov8n.pt to 'yolov8n.pt'...\n"
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+ ]
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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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+ "100%|██████████| 6.23M/6.23M [00:00<00:00, 15.2MB/s]\n"
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+ ]
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+ },
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+ {
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+ "name": "stdout",
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+ "output_type": "stream",
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+ "text": [
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+ "\n",
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+ "\n",
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+ "WARNING ⚠️ inference results will accumulate in RAM unless `stream=True` is passed, causing potential out-of-memory\n",
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+ "errors for large sources or long-running streams and videos. See https://docs.ultralytics.com/modes/predict/ for help.\n",
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+ "\n",
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+ "Example:\n",
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+ " results = model(source=..., stream=True) # generator of Results objects\n",
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+ " for r in results:\n",
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+ " boxes = r.boxes # Boxes object for bbox outputs\n",
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+ " masks = r.masks # Masks object for segment masks outputs\n",
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+ " probs = r.probs # Class probabilities for classification outputs\n",
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+ "\n",
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