Created using Colaboratory

baselhusam · Mar 31, 2023 · 986147a · 986147a
1 parent 3e912c2
commit 986147a
Showing 1 changed file with 48 additions and 42 deletions.
diff --git a/YOLO_Training.ipynb b/YOLO_Training.ipynb
@@ -1,14 +1,43 @@
 {
+  "nbformat": 4,
+  "nbformat_minor": 0,
+  "metadata": {
+    "colab": {
+      "provenance": [],
+      "mount_file_id": "1MUexEIOhBloFzM0VO8XE1ovz4vgKiHI_",
+      "authorship_tag": "ABX9TyMaKkd7iRV75npYFFkq8dk9",
+      "include_colab_link": true
+    },
+    "kernelspec": {
+      "name": "python3",
+      "display_name": "Python 3"
+    },
+    "language_info": {
+      "name": "python"
+    },
+    "accelerator": "GPU",
+    "gpuClass": "standard"
+  },
   "cells": [
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "aJjdD9NV8Sji"
+        "id": "view-in-github",
+        "colab_type": "text"
       },
       "source": [
-        "### Build a model for Face Detection with `Yolov8`"
+        "<a href=\"https://colab.research.google.com/github/baselhusam/Face-Blurring/blob/main/YOLO_Training.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "source": [
+        "### Build a model for Face Detection with `Yolov8`"
+      ],
+      "metadata": {
+        "id": "aJjdD9NV8Sji"
+      }
+    },
     {
       "cell_type": "code",
       "execution_count": null,
@@ -23,24 +52,21 @@
     },
     {
       "cell_type": "code",
-      "execution_count": null,
-      "metadata": {
-        "id": "AbNKGTKgHO0U"
-      },
-      "outputs": [],
       "source": [
         "# Import Yolo\n",
         "from ultralytics import YOLO\n",
         "\n",
         "# Build the model\n",
         "model = YOLO('yolov8n.pt')"
-      ]
+      ],
+      "metadata": {
+        "id": "AbNKGTKgHO0U"
+      },
+      "execution_count": null,
+      "outputs": []
     },
     {
       "cell_type": "markdown",
-      "metadata": {
-        "id": "IpVxGErQ8_zQ"
-      },
       "source": [
         "#### Train the Model\n",
         "\n",
@@ -50,22 +76,28 @@
         "* `epochs` : number of epochs, 100 in this case\n",
         "* `optimizer` : the `Adam` optimizer in this case\n",
         "* `batch` : 16 in this case"
-      ]
+      ],
+      "metadata": {
+        "id": "IpVxGErQ8_zQ"
+      }
     },
     {
       "cell_type": "code",
-      "execution_count": null,
+      "source": [
+        "model.train(data = '/content/drive/MyDrive/progressSoft/yolov8n.yaml',epochs = 100, optimizer= 'Adam', batch=16)"
+      ],
       "metadata": {
         "colab": {
           "base_uri": "https://localhost:8080/"
         },
         "id": "oHtC1jwiHwGT",
         "outputId": "b3314ca2-d62d-42c1-988e-d885bbe611c9"
       },
+      "execution_count": null,
       "outputs": [
         {
-          "name": "stderr",
           "output_type": "stream",
+          "name": "stderr",
           "text": [
             "Ultralytics YOLOv8.0.39 🚀 Python-3.8.10 torch-1.13.1+cu116 CUDA:0 (Tesla T4, 15110MiB)\n",
             "\u001b[34m\u001b[1myolo/engine/trainer: \u001b[0mtask=detect, mode=train, model=yolov8n.pt, data=/content/drive/MyDrive/progressSoft/yolov8n.yaml, epochs=100, patience=50, batch=16, imgsz=640, save=True, save_period=-1, cache=False, device=None, workers=8, project=None, name=None, exist_ok=False, pretrained=False, optimizer=Adam, verbose=True, seed=0, deterministic=True, single_cls=False, image_weights=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, min_memory=False, overlap_mask=True, mask_ratio=4, dropout=False, val=True, split=val, save_json=False, save_hybrid=False, conf=0.001, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=ultralytics/assets/, show=False, save_txt=False, save_conf=False, save_crop=False, hide_labels=False, hide_conf=False, vid_stride=1, line_thickness=3, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.001, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, fl_gamma=0.0, 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, mosaic=0.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, tracker=botsort, tracker_cfg=None, save_dir=runs/detect/train11\n",
@@ -621,33 +653,7 @@
             "Results saved to \u001b[1mruns/detect/train11\u001b[0m\n"
           ]
         }
-      ],
-      "source": [
-        "model.train(data = '/content/drive/MyDrive/progressSoft/yolov8n.yaml',epochs = 100, optimizer= 'Adam', batch=16)"
       ]
     }
-  ],
-  "metadata": {
-    "accelerator": "GPU",
-    "colab": {
-      "provenance": []
-    },
-    "gpuClass": "standard",
-    "kernelspec": {
-      "display_name": "base",
-      "language": "python",
-      "name": "python3"
-    },
-    "language_info": {
-      "name": "python",
-      "version": "3.9.13"
-    },
-    "vscode": {
-      "interpreter": {
-        "hash": "49cb93f377a7abe7414b7b0f21fb3017538004a126cf690fb524202736b7fb92"
-      }
-    }
-  },
-  "nbformat": 4,
-  "nbformat_minor": 0
-}
+  ]
+}