diff --git a/train_yolo.ipynb b/train_yolo.ipynb
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+++ b/train_yolo.ipynb
@@ -0,0 +1,258038 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "fatal: destination path 'ultralytics' already exists and is not an empty directory.\n",
+ "/home/parallels/Desktop/trap/ultralytics\n",
+ "HEAD is now at 6806f153 Fix `model.end2end` assert (#17391)\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages/IPython/core/magics/osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n",
+ " self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "--2025-01-23 23:23:23-- https://gist.githubusercontent.com/Y-T-G/8f4fc0b78a0a559a06fe84ae4f359e6e/raw/f8e9ba1644cbfa86295f14fbe26c3d91a504b155/add_head.patch\n",
+ "Resolving gist.githubusercontent.com (gist.githubusercontent.com)... 185.199.110.133, 185.199.111.133, 185.199.109.133, ...\n",
+ "Connecting to gist.githubusercontent.com (gist.githubusercontent.com)|185.199.110.133|:443... connected.\n",
+ "HTTP request sent, awaiting response... 200 OK\n",
+ "Length: 11324 (11K) [text/plain]\n",
+ "Saving to: ‘add_head.patch.1’\n",
+ "\n",
+ "add_head.patch.1 100%[===================>] 11.06K --.-KB/s in 0.003s \n",
+ "\n",
+ "2025-01-23 23:23:23 (3.46 MB/s) - ‘add_head.patch.1’ saved [11324/11324]\n",
+ "\n",
+ "error: ultralytics/cfg/models/v8/yolov8n-2xhead.yaml: already exists in working directory\n",
+ "Requirement already satisfied: pip in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (24.3.1)\n",
+ "Obtaining file:///home/parallels/Desktop/trap/ultralytics\n",
+ " Installing build dependencies ... \u001b[?25ldone\n",
+ "\u001b[?25h Checking if build backend supports build_editable ... \u001b[?25ldone\n",
+ "\u001b[?25h Getting requirements to build editable ... \u001b[?25ldone\n",
+ "\u001b[?25h Preparing editable metadata (pyproject.toml) ... \u001b[?25ldone\n",
+ "\u001b[?25hRequirement already satisfied: numpy>=1.23.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (1.26.4)\n",
+ "Requirement already satisfied: matplotlib>=3.3.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (3.5.3)\n",
+ "Requirement already satisfied: opencv-python>=4.6.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (4.10.0.84)\n",
+ "Requirement already satisfied: pillow>=7.1.2 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (11.0.0)\n",
+ "Requirement already satisfied: pyyaml>=5.3.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (6.0.2)\n",
+ "Requirement already satisfied: requests>=2.23.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (2.32.3)\n",
+ "Requirement already satisfied: scipy>=1.4.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (1.14.1)\n",
+ "Requirement already satisfied: torch>=1.8.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (2.5.1)\n",
+ "Requirement already satisfied: torchvision>=0.9.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (0.20.1)\n",
+ "Requirement already satisfied: tqdm>=4.64.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (4.67.1)\n",
+ "Requirement already satisfied: psutil in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (6.1.0)\n",
+ "Requirement already satisfied: py-cpuinfo in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (9.0.0)\n",
+ "Requirement already satisfied: pandas>=1.1.4 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (2.2.3)\n",
+ "Requirement already satisfied: seaborn>=0.11.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (0.13.2)\n",
+ "Requirement already satisfied: ultralytics-thop>=2.0.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from ultralytics==8.3.28) (2.0.13)\n",
+ "Requirement already satisfied: cycler>=0.10 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (0.12.1)\n",
+ "Requirement already satisfied: fonttools>=4.22.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (4.55.3)\n",
+ "Requirement already satisfied: kiwisolver>=1.0.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (1.4.7)\n",
+ "Requirement already satisfied: packaging>=20.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (24.2)\n",
+ "Requirement already satisfied: pyparsing>=2.2.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (3.2.0)\n",
+ "Requirement already satisfied: python-dateutil>=2.7 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from matplotlib>=3.3.0->ultralytics==8.3.28) (2.9.0.post0)\n",
+ "Requirement already satisfied: pytz>=2020.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from pandas>=1.1.4->ultralytics==8.3.28) (2024.2)\n",
+ "Requirement already satisfied: tzdata>=2022.7 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from pandas>=1.1.4->ultralytics==8.3.28) (2024.2)\n",
+ "Requirement already satisfied: charset-normalizer<4,>=2 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from requests>=2.23.0->ultralytics==8.3.28) (3.4.0)\n",
+ "Requirement already satisfied: idna<4,>=2.5 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from requests>=2.23.0->ultralytics==8.3.28) (3.10)\n",
+ "Requirement already satisfied: urllib3<3,>=1.21.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from requests>=2.23.0->ultralytics==8.3.28) (2.2.3)\n",
+ "Requirement already satisfied: certifi>=2017.4.17 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from requests>=2.23.0->ultralytics==8.3.28) (2024.8.30)\n",
+ "Requirement already satisfied: filelock in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (3.16.1)\n",
+ "Requirement already satisfied: typing-extensions>=4.8.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (4.12.2)\n",
+ "Requirement already satisfied: networkx in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (3.4.2)\n",
+ "Requirement already satisfied: jinja2 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (3.1.4)\n",
+ "Requirement already satisfied: fsspec in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (2024.12.0)\n",
+ "Requirement already satisfied: sympy==1.13.1 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from torch>=1.8.0->ultralytics==8.3.28) (1.13.1)\n",
+ "Requirement already satisfied: mpmath<1.4,>=1.1.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from sympy==1.13.1->torch>=1.8.0->ultralytics==8.3.28) (1.3.0)\n",
+ "Requirement already satisfied: six>=1.5 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from python-dateutil>=2.7->matplotlib>=3.3.0->ultralytics==8.3.28) (1.17.0)\n",
+ "Requirement already satisfied: MarkupSafe>=2.0 in /home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages (from jinja2->torch>=1.8.0->ultralytics==8.3.28) (3.0.2)\n",
+ "Building wheels for collected packages: ultralytics\n",
+ " Building editable for ultralytics (pyproject.toml) ... \u001b[?25ldone\n",
+ "\u001b[?25h Created wheel for ultralytics: filename=ultralytics-8.3.28-0.editable-py3-none-any.whl size=23780 sha256=6e99284e12ea38418e2f6576702f97c041b593acb3472f0a51743b897ab2a481\n",
+ " Stored in directory: /tmp/pip-ephem-wheel-cache-nb2e2mem/wheels/b1/33/35/e8ab0ce4c6b13598bfa81846c3a6d48cfca86ecf10f3f1c78b\n",
+ "Successfully built ultralytics\n",
+ "Installing collected packages: ultralytics\n",
+ " Attempting uninstall: ultralytics\n",
+ " Found existing installation: ultralytics 8.3.28\n",
+ " Uninstalling ultralytics-8.3.28:\n",
+ " Successfully uninstalled ultralytics-8.3.28\n",
+ "Successfully installed ultralytics-8.3.28\n"
+ ]
+ }
+ ],
+ "source": [
+ "!git clone https://github.com/ultralytics/ultralytics\n",
+ "%cd ./ultralytics\n",
+ "!git reset --hard 6806f15396432fffb951250d650454b840eb4c28\n",
+ "!wget https://gist.githubusercontent.com/Y-T-G/8f4fc0b78a0a559a06fe84ae4f359e6e/raw/f8e9ba1644cbfa86295f14fbe26c3d91a504b155/add_head.patch\n",
+ "!git apply add_head.patch\n",
+ "!/home/parallels/.pyenv/versions/3.10.4/envs/trap_env/bin/python -m pip install --upgrade pip\n",
+ "!pip install -e ."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Train Single Head with Top-down dataset"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Download the dataset from here: https://github.com/ucuapps/top-view-multi-person-tracking/tree/master"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "{'status': 'ok', 'restart': True}"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Reset runtime\n",
+ "import IPython\n",
+ "IPython.Application.instance().kernel.do_shutdown(True)\n",
+ "\n",
+ "# Wait for restart and then continue"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "100%|██████████| 2/2 [00:00<00:00, 5652.70it/s]\n",
+ "100%|██████████| 2/2 [00:00<00:00, 9845.78it/s]\n"
+ ]
+ },
+ {
+ "ename": "",
+ "evalue": "",
+ "output_type": "error",
+ "traceback": [
+ "\u001b[1;31mThe Kernel crashed while executing code in the current cell or a previous cell. \n",
+ "\u001b[1;31mPlease review the code in the cell(s) to identify a possible cause of the failure. \n",
+ "\u001b[1;31mClick here for more info. \n",
+ "\u001b[1;31mView Jupyter log for further details."
+ ]
+ }
+ ],
+ "source": [
+ "from tqdm import tqdm\n",
+ "import os\n",
+ "import yaml\n",
+ "import shutil\n",
+ "\n",
+ "def send_to_directories(data_dir):\n",
+ " image_dir = f'{data_dir}/images'\n",
+ " label_dir = f'{data_dir}/labels'\n",
+ " os.makedirs(image_dir, exist_ok=True)\n",
+ " os.makedirs(label_dir, exist_ok=True)\n",
+ " \n",
+ " for file_name in tqdm(os.listdir(data_dir)):\n",
+ " if file_name[-4:] == \".jpg\":\n",
+ " src_path = os.path.join(data_dir, file_name)\n",
+ " dst_path = os.path.join(image_dir, file_name)\n",
+ " shutil.move(src_path, dst_path)\n",
+ " elif file_name[-4:] == \".txt\":\n",
+ " src_path = os.path.join(data_dir, file_name)\n",
+ " dst_path = os.path.join(label_dir, file_name)\n",
+ " shutil.move(src_path, dst_path)\n",
+ "\n",
+ " # image_path = f'{image_dir}/{i:06d}.jpg'\n",
+ " # label_path = f'{label_dir}/{i:06d}.txt'\n",
+ " # image = d['image'].resize((640, 640))\n",
+ " # image.save(image_path)\n",
+ " \n",
+ " # image_source, image = load_image(image_path)\n",
+ " # boxes, logits, phrases = run_dino(dino, image)\n",
+ "\n",
+ " # label = ['0 ' + ' '.join(list(map(str, b))) for b in boxes.tolist()]\n",
+ " # label = '\\n'.join(label)\n",
+ " # with open(label_path, 'w') as f:\n",
+ " # f.write(label)\n",
+ "\n",
+ "\n",
+ "send_to_directories('top_down_data/train')\n",
+ "send_to_directories('top_down_data/val')\n",
+ "\n",
+ "config = {\n",
+ " 'names': ['top-down-person'],\n",
+ " 'nc': 1,\n",
+ " 'train': './train/images',\n",
+ " 'val': './val/images'\n",
+ "}\n",
+ "\n",
+ "with open('top_down_data/data.yaml', 'w') as f:\n",
+ " yaml.dump(config, f)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "/home/parallels/Desktop/trap/ultralytics\n"
+ ]
+ },
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/home/parallels/.pyenv/versions/3.10.4/envs/trap_env/lib/python3.10/site-packages/IPython/core/magics/osm.py:417: UserWarning: This is now an optional IPython functionality, setting dhist requires you to install the `pickleshare` library.\n",
+ " self.shell.db['dhist'] = compress_dhist(dhist)[-100:]\n"
+ ]
+ }
+ ],
+ "source": [
+ "%pwd\n",
+ "%cd ./ultralytics"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from ultralytics import YOLO\n",
+ "import torch\n",
+ "import copy"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "model = YOLO(\"yolov8n.pt\") # load a pretrained model (recommended for training)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Keep a copy of old state dict for sanity check\n",
+ "old_dict = copy.deepcopy(model.state_dict())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "odict_keys(['model.model.0.conv.weight', 'model.model.0.bn.weight', 'model.model.0.bn.bias', 'model.model.0.bn.running_mean', 'model.model.0.bn.running_var', 'model.model.0.bn.num_batches_tracked', 'model.model.1.conv.weight', 'model.model.1.bn.weight', 'model.model.1.bn.bias', 'model.model.1.bn.running_mean', 'model.model.1.bn.running_var', 'model.model.1.bn.num_batches_tracked', 'model.model.2.cv1.conv.weight', 'model.model.2.cv1.bn.weight', 'model.model.2.cv1.bn.bias', 'model.model.2.cv1.bn.running_mean', 'model.model.2.cv1.bn.running_var', 'model.model.2.cv1.bn.num_batches_tracked', 'model.model.2.cv2.conv.weight', 'model.model.2.cv2.bn.weight', 'model.model.2.cv2.bn.bias', 'model.model.2.cv2.bn.running_mean', 'model.model.2.cv2.bn.running_var', 'model.model.2.cv2.bn.num_batches_tracked', 'model.model.2.m.0.cv1.conv.weight', 'model.model.2.m.0.cv1.bn.weight', 'model.model.2.m.0.cv1.bn.bias', 'model.model.2.m.0.cv1.bn.running_mean', 'model.model.2.m.0.cv1.bn.running_var', 'model.model.2.m.0.cv1.bn.num_batches_tracked', 'model.model.2.m.0.cv2.conv.weight', 'model.model.2.m.0.cv2.bn.weight', 'model.model.2.m.0.cv2.bn.bias', 'model.model.2.m.0.cv2.bn.running_mean', 'model.model.2.m.0.cv2.bn.running_var', 'model.model.2.m.0.cv2.bn.num_batches_tracked', 'model.model.3.conv.weight', 'model.model.3.bn.weight', 'model.model.3.bn.bias', 'model.model.3.bn.running_mean', 'model.model.3.bn.running_var', 'model.model.3.bn.num_batches_tracked', 'model.model.4.cv1.conv.weight', 'model.model.4.cv1.bn.weight', 'model.model.4.cv1.bn.bias', 'model.model.4.cv1.bn.running_mean', 'model.model.4.cv1.bn.running_var', 'model.model.4.cv1.bn.num_batches_tracked', 'model.model.4.cv2.conv.weight', 'model.model.4.cv2.bn.weight', 'model.model.4.cv2.bn.bias', 'model.model.4.cv2.bn.running_mean', 'model.model.4.cv2.bn.running_var', 'model.model.4.cv2.bn.num_batches_tracked', 'model.model.4.m.0.cv1.conv.weight', 'model.model.4.m.0.cv1.bn.weight', 'model.model.4.m.0.cv1.bn.bias', 'model.model.4.m.0.cv1.bn.running_mean', 'model.model.4.m.0.cv1.bn.running_var', 'model.model.4.m.0.cv1.bn.num_batches_tracked', 'model.model.4.m.0.cv2.conv.weight', 'model.model.4.m.0.cv2.bn.weight', 'model.model.4.m.0.cv2.bn.bias', 'model.model.4.m.0.cv2.bn.running_mean', 'model.model.4.m.0.cv2.bn.running_var', 'model.model.4.m.0.cv2.bn.num_batches_tracked', 'model.model.4.m.1.cv1.conv.weight', 'model.model.4.m.1.cv1.bn.weight', 'model.model.4.m.1.cv1.bn.bias', 'model.model.4.m.1.cv1.bn.running_mean', 'model.model.4.m.1.cv1.bn.running_var', 'model.model.4.m.1.cv1.bn.num_batches_tracked', 'model.model.4.m.1.cv2.conv.weight', 'model.model.4.m.1.cv2.bn.weight', 'model.model.4.m.1.cv2.bn.bias', 'model.model.4.m.1.cv2.bn.running_mean', 'model.model.4.m.1.cv2.bn.running_var', 'model.model.4.m.1.cv2.bn.num_batches_tracked', 'model.model.5.conv.weight', 'model.model.5.bn.weight', 'model.model.5.bn.bias', 'model.model.5.bn.running_mean', 'model.model.5.bn.running_var', 'model.model.5.bn.num_batches_tracked', 'model.model.6.cv1.conv.weight', 'model.model.6.cv1.bn.weight', 'model.model.6.cv1.bn.bias', 'model.model.6.cv1.bn.running_mean', 'model.model.6.cv1.bn.running_var', 'model.model.6.cv1.bn.num_batches_tracked', 'model.model.6.cv2.conv.weight', 'model.model.6.cv2.bn.weight', 'model.model.6.cv2.bn.bias', 'model.model.6.cv2.bn.running_mean', 'model.model.6.cv2.bn.running_var', 'model.model.6.cv2.bn.num_batches_tracked', 'model.model.6.m.0.cv1.conv.weight', 'model.model.6.m.0.cv1.bn.weight', 'model.model.6.m.0.cv1.bn.bias', 'model.model.6.m.0.cv1.bn.running_mean', 'model.model.6.m.0.cv1.bn.running_var', 'model.model.6.m.0.cv1.bn.num_batches_tracked', 'model.model.6.m.0.cv2.conv.weight', 'model.model.6.m.0.cv2.bn.weight', 'model.model.6.m.0.cv2.bn.bias', 'model.model.6.m.0.cv2.bn.running_mean', 'model.model.6.m.0.cv2.bn.running_var', 'model.model.6.m.0.cv2.bn.num_batches_tracked', 'model.model.6.m.1.cv1.conv.weight', 'model.model.6.m.1.cv1.bn.weight', 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'model.model.8.cv2.bn.num_batches_tracked', 'model.model.8.m.0.cv1.conv.weight', 'model.model.8.m.0.cv1.bn.weight', 'model.model.8.m.0.cv1.bn.bias', 'model.model.8.m.0.cv1.bn.running_mean', 'model.model.8.m.0.cv1.bn.running_var', 'model.model.8.m.0.cv1.bn.num_batches_tracked', 'model.model.8.m.0.cv2.conv.weight', 'model.model.8.m.0.cv2.bn.weight', 'model.model.8.m.0.cv2.bn.bias', 'model.model.8.m.0.cv2.bn.running_mean', 'model.model.8.m.0.cv2.bn.running_var', 'model.model.8.m.0.cv2.bn.num_batches_tracked', 'model.model.9.cv1.conv.weight', 'model.model.9.cv1.bn.weight', 'model.model.9.cv1.bn.bias', 'model.model.9.cv1.bn.running_mean', 'model.model.9.cv1.bn.running_var', 'model.model.9.cv1.bn.num_batches_tracked', 'model.model.9.cv2.conv.weight', 'model.model.9.cv2.bn.weight', 'model.model.9.cv2.bn.bias', 'model.model.9.cv2.bn.running_mean', 'model.model.9.cv2.bn.running_var', 'model.model.9.cv2.bn.num_batches_tracked', 'model.model.12.cv1.conv.weight', 'model.model.12.cv1.bn.weight', 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'model.model.18.cv1.conv.weight', 'model.model.18.cv1.bn.weight', 'model.model.18.cv1.bn.bias', 'model.model.18.cv1.bn.running_mean', 'model.model.18.cv1.bn.running_var', 'model.model.18.cv1.bn.num_batches_tracked', 'model.model.18.cv2.conv.weight', 'model.model.18.cv2.bn.weight', 'model.model.18.cv2.bn.bias', 'model.model.18.cv2.bn.running_mean', 'model.model.18.cv2.bn.running_var', 'model.model.18.cv2.bn.num_batches_tracked', 'model.model.18.m.0.cv1.conv.weight', 'model.model.18.m.0.cv1.bn.weight', 'model.model.18.m.0.cv1.bn.bias', 'model.model.18.m.0.cv1.bn.running_mean', 'model.model.18.m.0.cv1.bn.running_var', 'model.model.18.m.0.cv1.bn.num_batches_tracked', 'model.model.18.m.0.cv2.conv.weight', 'model.model.18.m.0.cv2.bn.weight', 'model.model.18.m.0.cv2.bn.bias', 'model.model.18.m.0.cv2.bn.running_mean', 'model.model.18.m.0.cv2.bn.running_var', 'model.model.18.m.0.cv2.bn.num_batches_tracked', 'model.model.19.conv.weight', 'model.model.19.bn.weight', 'model.model.19.bn.bias', 'model.model.19.bn.running_mean', 'model.model.19.bn.running_var', 'model.model.19.bn.num_batches_tracked', 'model.model.21.cv1.conv.weight', 'model.model.21.cv1.bn.weight', 'model.model.21.cv1.bn.bias', 'model.model.21.cv1.bn.running_mean', 'model.model.21.cv1.bn.running_var', 'model.model.21.cv1.bn.num_batches_tracked', 'model.model.21.cv2.conv.weight', 'model.model.21.cv2.bn.weight', 'model.model.21.cv2.bn.bias', 'model.model.21.cv2.bn.running_mean', 'model.model.21.cv2.bn.running_var', 'model.model.21.cv2.bn.num_batches_tracked', 'model.model.21.m.0.cv1.conv.weight', 'model.model.21.m.0.cv1.bn.weight', 'model.model.21.m.0.cv1.bn.bias', 'model.model.21.m.0.cv1.bn.running_mean', 'model.model.21.m.0.cv1.bn.running_var', 'model.model.21.m.0.cv1.bn.num_batches_tracked', 'model.model.21.m.0.cv2.conv.weight', 'model.model.21.m.0.cv2.bn.weight', 'model.model.21.m.0.cv2.bn.bias', 'model.model.21.m.0.cv2.bn.running_mean', 'model.model.21.m.0.cv2.bn.running_var', 'model.model.21.m.0.cv2.bn.num_batches_tracked', 'model.model.22.cv2.0.0.conv.weight', 'model.model.22.cv2.0.0.bn.weight', 'model.model.22.cv2.0.0.bn.bias', 'model.model.22.cv2.0.0.bn.running_mean', 'model.model.22.cv2.0.0.bn.running_var', 'model.model.22.cv2.0.0.bn.num_batches_tracked', 'model.model.22.cv2.0.1.conv.weight', 'model.model.22.cv2.0.1.bn.weight', 'model.model.22.cv2.0.1.bn.bias', 'model.model.22.cv2.0.1.bn.running_mean', 'model.model.22.cv2.0.1.bn.running_var', 'model.model.22.cv2.0.1.bn.num_batches_tracked', 'model.model.22.cv2.0.2.weight', 'model.model.22.cv2.0.2.bias', 'model.model.22.cv2.1.0.conv.weight', 'model.model.22.cv2.1.0.bn.weight', 'model.model.22.cv2.1.0.bn.bias', 'model.model.22.cv2.1.0.bn.running_mean', 'model.model.22.cv2.1.0.bn.running_var', 'model.model.22.cv2.1.0.bn.num_batches_tracked', 'model.model.22.cv2.1.1.conv.weight', 'model.model.22.cv2.1.1.bn.weight', 'model.model.22.cv2.1.1.bn.bias', 'model.model.22.cv2.1.1.bn.running_mean', 'model.model.22.cv2.1.1.bn.running_var', 'model.model.22.cv2.1.1.bn.num_batches_tracked', 'model.model.22.cv2.1.2.weight', 'model.model.22.cv2.1.2.bias', 'model.model.22.cv2.2.0.conv.weight', 'model.model.22.cv2.2.0.bn.weight', 'model.model.22.cv2.2.0.bn.bias', 'model.model.22.cv2.2.0.bn.running_mean', 'model.model.22.cv2.2.0.bn.running_var', 'model.model.22.cv2.2.0.bn.num_batches_tracked', 'model.model.22.cv2.2.1.conv.weight', 'model.model.22.cv2.2.1.bn.weight', 'model.model.22.cv2.2.1.bn.bias', 'model.model.22.cv2.2.1.bn.running_mean', 'model.model.22.cv2.2.1.bn.running_var', 'model.model.22.cv2.2.1.bn.num_batches_tracked', 'model.model.22.cv2.2.2.weight', 'model.model.22.cv2.2.2.bias', 'model.model.22.cv3.0.0.conv.weight', 'model.model.22.cv3.0.0.bn.weight', 'model.model.22.cv3.0.0.bn.bias', 'model.model.22.cv3.0.0.bn.running_mean', 'model.model.22.cv3.0.0.bn.running_var', 'model.model.22.cv3.0.0.bn.num_batches_tracked', 'model.model.22.cv3.0.1.conv.weight', 'model.model.22.cv3.0.1.bn.weight', 'model.model.22.cv3.0.1.bn.bias', 'model.model.22.cv3.0.1.bn.running_mean', 'model.model.22.cv3.0.1.bn.running_var', 'model.model.22.cv3.0.1.bn.num_batches_tracked', 'model.model.22.cv3.0.2.weight', 'model.model.22.cv3.0.2.bias', 'model.model.22.cv3.1.0.conv.weight', 'model.model.22.cv3.1.0.bn.weight', 'model.model.22.cv3.1.0.bn.bias', 'model.model.22.cv3.1.0.bn.running_mean', 'model.model.22.cv3.1.0.bn.running_var', 'model.model.22.cv3.1.0.bn.num_batches_tracked', 'model.model.22.cv3.1.1.conv.weight', 'model.model.22.cv3.1.1.bn.weight', 'model.model.22.cv3.1.1.bn.bias', 'model.model.22.cv3.1.1.bn.running_mean', 'model.model.22.cv3.1.1.bn.running_var', 'model.model.22.cv3.1.1.bn.num_batches_tracked', 'model.model.22.cv3.1.2.weight', 'model.model.22.cv3.1.2.bias', 'model.model.22.cv3.2.0.conv.weight', 'model.model.22.cv3.2.0.bn.weight', 'model.model.22.cv3.2.0.bn.bias', 'model.model.22.cv3.2.0.bn.running_mean', 'model.model.22.cv3.2.0.bn.running_var', 'model.model.22.cv3.2.0.bn.num_batches_tracked', 'model.model.22.cv3.2.1.conv.weight', 'model.model.22.cv3.2.1.bn.weight', 'model.model.22.cv3.2.1.bn.bias', 'model.model.22.cv3.2.1.bn.running_mean', 'model.model.22.cv3.2.1.bn.running_var', 'model.model.22.cv3.2.1.bn.num_batches_tracked', 'model.model.22.cv3.2.2.weight', 'model.model.22.cv3.2.2.bias', 'model.model.22.dfl.conv.weight'])"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# We should freeze all but the last layer\n",
+ "model.state_dict().keys()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Add a callback to put the frozen layers in eval mode to prevent BN values\n",
+ "# from changing.\n",
+ "def put_in_eval_mode(trainer, n_layers=22):\n",
+ " for i, (name, module) in enumerate(trainer.model.named_modules()):\n",
+ " if name.endswith(\"bn\") and int(name.split('.')[1]) < n_layers:\n",
+ " module.eval()\n",
+ " module.track_running_stats = False\n",
+ " # print(name, \" put in eval mode.\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "model.add_callback(\"on_train_epoch_start\", put_in_eval_mode)\n",
+ "model.add_callback(\"on_pretrain_routine_start\", put_in_eval_mode)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "New https://pypi.org/project/ultralytics/8.3.62 available 😃 Update with 'pip install -U ultralytics'\n",
+ "Ultralytics 8.3.28 🚀 Python-3.10.4 torch-2.5.1 CPU (-)\n",
+ "\u001b[34m\u001b[1mengine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=/home/parallels/Desktop/trap/top_down_data/data.yaml, epochs=20, time=None, patience=100, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=mps, workers=8, project=None, name=train8, exist_ok=False, pretrained=True, optimizer=auto, verbose=True, seed=0, deterministic=True, single_cls=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, amp=True, fraction=1.0, profile=False, freeze=22, multi_scale=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, split=val, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, vid_stride=1, stream_buffer=False, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, embed=None, show=False, save_frames=False, save_txt=False, save_conf=False, save_crop=False, show_labels=True, show_conf=True, show_boxes=True, line_width=None, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=True, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, pose=12.0, kobj=1.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, bgr=0.0, mosaic=1.0, mixup=0.0, copy_paste=0.0, copy_paste_mode=flip, auto_augment=randaugment, erasing=0.4, crop_fraction=1.0, cfg=None, tracker=botsort.yaml, save_dir=/home/parallels/.pyenv/runs/detect/train8\n",
+ "\n",
+ " from n params module arguments \n",
+ " 0 -1 1 464 ultralytics.nn.modules.conv.Conv [3, 16, 3, 2] \n",
+ " 1 -1 1 4672 ultralytics.nn.modules.conv.Conv [16, 32, 3, 2] \n",
+ " 2 -1 1 7360 ultralytics.nn.modules.block.C2f [32, 32, 1, True] \n",
+ " 3 -1 1 18560 ultralytics.nn.modules.conv.Conv [32, 64, 3, 2] \n",
+ " 4 -1 2 49664 ultralytics.nn.modules.block.C2f [64, 64, 2, True] \n",
+ " 5 -1 1 73984 ultralytics.nn.modules.conv.Conv [64, 128, 3, 2] \n",
+ " 6 -1 2 197632 ultralytics.nn.modules.block.C2f [128, 128, 2, True] \n",
+ " 7 -1 1 295424 ultralytics.nn.modules.conv.Conv [128, 256, 3, 2] \n",
+ " 8 -1 1 460288 ultralytics.nn.modules.block.C2f [256, 256, 1, True] \n",
+ " 9 -1 1 164608 ultralytics.nn.modules.block.SPPF [256, 256, 5] \n",
+ " 10 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
+ " 11 [-1, 6] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
+ " 12 -1 1 148224 ultralytics.nn.modules.block.C2f [384, 128, 1] \n",
+ " 13 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest'] \n",
+ " 14 [-1, 4] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
+ " 15 -1 1 37248 ultralytics.nn.modules.block.C2f [192, 64, 1] \n",
+ " 16 -1 1 36992 ultralytics.nn.modules.conv.Conv [64, 64, 3, 2] \n",
+ " 17 [-1, 12] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
+ " 18 -1 1 123648 ultralytics.nn.modules.block.C2f [192, 128, 1] \n",
+ " 19 -1 1 147712 ultralytics.nn.modules.conv.Conv [128, 128, 3, 2] \n",
+ " 20 [-1, 9] 1 0 ultralytics.nn.modules.conv.Concat [1] \n",
+ " 21 -1 1 493056 ultralytics.nn.modules.block.C2f [384, 256, 1] \n",
+ " 22 [15, 18, 21] 1 751507 ultralytics.nn.modules.head.Detect [1, [64, 128, 256]] \n",
+ "Model summary: 225 layers, 3,011,043 parameters, 3,011,027 gradients, 8.2 GFLOPs\n",
+ "\n",
+ "Transferred 355/355 items from pretrained weights\n",
+ "\u001b[34m\u001b[1mTensorBoard: \u001b[0mStart with 'tensorboard --logdir /home/parallels/.pyenv/runs/detect/train8', view at http://localhost:6006/\n",
+ "Freezing layer 'model.0.conv.weight'\n",
+ "Freezing layer 'model.0.bn.weight'\n",
+ "Freezing layer 'model.0.bn.bias'\n",
+ "Freezing layer 'model.1.conv.weight'\n",
+ "Freezing layer 'model.1.bn.weight'\n",
+ "Freezing layer 'model.1.bn.bias'\n",
+ "Freezing layer 'model.2.cv1.conv.weight'\n",
+ "Freezing layer 'model.2.cv1.bn.weight'\n",
+ "Freezing layer 'model.2.cv1.bn.bias'\n",
+ "Freezing layer 'model.2.cv2.conv.weight'\n",
+ "Freezing layer 'model.2.cv2.bn.weight'\n",
+ "Freezing layer 'model.2.cv2.bn.bias'\n",
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