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{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from ultralytics import YOLO\n",
"import torch\n",
"from PIL import Image, ImageDraw, ImageFont\n",
"import numpy as np\n",
"import infer"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from importlib import reload\n",
"reload(infer)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"device = 'cuda' if torch.cuda.is_available() else 'cpu'\n",
"model_pose = YOLO('yolov8l-pose.pt')\n",
"model_pose.to(device)\n",
"\n",
"model_det = YOLO('yolov8m.pt')\n",
"model_det.to(device);"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"url = \"image.jpg\"\n",
"results = model_pose(url)\n",
"results_det = model_det(url)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"def draw_output(image_pil: Image.Image, keypoints: dict): \n",
" draw = ImageDraw.Draw(image_pil)\n",
" line_width = 10\n",
" font = ImageFont.truetype(\"DejaVuSerif-Bold.ttf\", 70)\n",
" \n",
" ear, eye = None, None\n",
" if keypoints[\"left_ear\"] and keypoints[\"left_eye\"]:\n",
" ear = keypoints[\"left_ear\"]\n",
" eye = keypoints[\"left_eye\"]\n",
" elif keypoints[\"right_ear\"] and keypoints[\"right_eye\"]:\n",
" ear = keypoints[\"right_ear\"]\n",
" eye = keypoints[\"right_eye\"]\n",
" \n",
" # draw extended left and right eye lines\n",
" if ear and eye:\n",
" left_new_point = infer.extend_line(ear, eye, 3)\n",
" l1 = [ear, left_new_point]\n",
" draw.line(l1, fill='red', width=line_width)\n",
" # draw a horizontal line from ear forwards\n",
" ear = np.array(ear)\n",
" l1 = np.array(l1)\n",
" l1_vector = l1[1] - l1[0]\n",
" x_s = np.sign(l1_vector)[0]\n",
" length_l1 = np.linalg.norm(l1_vector)\n",
" p2 = ear + np.array([length_l1*x_s, 0])\n",
" ear = tuple(ear.tolist())\n",
" l = [ear, tuple(p2.tolist())]\n",
" draw.line(l, fill='gray', width=line_width//2)\n",
" # draw angle\n",
" angle = infer.calculate_angle_to_horizontal(l1_vector)\n",
" draw.text(ear, f'{angle:.2f}', fill='red', font=font)\n",
" print(infer.get_eye_angles(keypoints))\n",
"\n",
"\n",
" # draw elbow angles\n",
" left_elbow_angle, right_elbow_angle = infer.get_elbow_angles(keypoints)\n",
" if left_elbow_angle:\n",
" draw.text(keypoints['left_elbow'], f'{left_elbow_angle:.2f}', fill='red', font=font)\n",
" # draw polyline for left arm\n",
" draw.line([keypoints['left_shoulder'], keypoints['left_elbow'], keypoints['left_wrist']], fill='blue', width=line_width)\n",
" if right_elbow_angle:\n",
" draw.text(keypoints['right_elbow'], f'{right_elbow_angle:.2f}', fill='red', font=font)\n",
" # draw polyline for right arm\n",
" draw.line([keypoints['right_shoulder'], keypoints['right_elbow'], keypoints['right_wrist']], fill='blue', width=line_width)\n",
"\n",
" return image_pil"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"keypoints = infer.get_keypoints(results[0])\n",
"img = Image.open(url)\n",
"img = draw_output(img, keypoints)\n",
"img.resize((800, 800))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
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