yolo_setup.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using cache found in /home/nick/.cache/torch/hub/ultralytics_yolov5_master\n",
      "YOLOv5 🚀 2023-3-27 Python-3.9.13 torch-2.0.0 CPU\n",
      "\n",
      "Fusing layers... \n",
      "YOLOv5s summary: 213 layers, 7225885 parameters, 0 gradients\n",
      "Adding AutoShape... \n"
     ]
    }
   ],
   "source": [
    "yolo_model = torch.hub.load('ultralytics/yolov5', 'yolov5s', pretrained=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "AutoShape(\n",
       "  (model): DetectMultiBackend(\n",
       "    (model): DetectionModel(\n",
       "      (model): Sequential(\n",
       "        (0): Conv(\n",
       "          (conv): Conv2d(3, 32, kernel_size=(6, 6), stride=(2, 2), padding=(2, 2))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (1): Conv(\n",
       "          (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (2): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(64, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(32, 32, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (3): Conv(\n",
       "          (conv): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (4): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(128, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (1): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (5): Conv(\n",
       "          (conv): Conv2d(128, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (6): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (1): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "            (2): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (7): Conv(\n",
       "          (conv): Conv2d(256, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (8): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (9): SPPF(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): MaxPool2d(kernel_size=5, stride=1, padding=2, dilation=1, ceil_mode=False)\n",
       "        )\n",
       "        (10): Conv(\n",
       "          (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (11): Upsample(scale_factor=2.0, mode='nearest')\n",
       "        (12): Concat()\n",
       "        (13): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (14): Conv(\n",
       "          (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (15): Upsample(scale_factor=2.0, mode='nearest')\n",
       "        (16): Concat()\n",
       "        (17): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (18): Conv(\n",
       "          (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (19): Concat()\n",
       "        (20): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (21): Conv(\n",
       "          (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))\n",
       "          (act): SiLU(inplace=True)\n",
       "        )\n",
       "        (22): Concat()\n",
       "        (23): C3(\n",
       "          (cv1): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv2): Conv(\n",
       "            (conv): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (cv3): Conv(\n",
       "            (conv): Conv2d(512, 512, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (act): SiLU(inplace=True)\n",
       "          )\n",
       "          (m): Sequential(\n",
       "            (0): Bottleneck(\n",
       "              (cv1): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(1, 1), stride=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "              (cv2): Conv(\n",
       "                (conv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1))\n",
       "                (act): SiLU(inplace=True)\n",
       "              )\n",
       "            )\n",
       "          )\n",
       "        )\n",
       "        (24): Detect(\n",
       "          (m): ModuleList(\n",
       "            (0): Conv2d(128, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (1): Conv2d(256, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "            (2): Conv2d(512, 255, kernel_size=(1, 1), stride=(1, 1))\n",
       "          )\n",
       "        )\n",
       "      )\n",
       "    )\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "yolo_model"
   ]
  }
 ],
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