test_anchors.ipynb

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 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize Anchor Boxes\n",
    "\n",
    "!OpenCV must be installed to run this notebook!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from keras_retinanet.bin.train import create_generators\n",
    "from keras_retinanet.models import backbone\n",
    "from keras_retinanet.utils.config import read_config_file,parse_anchor_parameters\n",
    "from keras_retinanet.bin.debug import run"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = backbone('resnet50')\n",
    "\n",
    "class args:\n",
    "    batch_size = 4\n",
    "    config = read_config_file('config.ini')\n",
    "    random_transform = True\n",
    "    annotations = 'annotations.csv'\n",
    "    val_annotations = 'val_annotations.csv'\n",
    "    classes = 'classes.csv'\n",
    "    image_min_side = 672\n",
    "    image_max_side = 672\n",
    "    dataset_type = 'csv'\n",
    "    tensorboard_dir = ''\n",
    "    evaluation = True\n",
    "    snapshots = True\n",
    "    snapshot_path = \"saved/\"\n",
    "    backbone = 'resnet50'\n",
    "    weighted_average = True\n",
    "    resize=True\n",
    "    anchors=True\n",
    "    \n",
    "train_gen,valid_gen = create_generators(args,b.preprocess_image)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "while run(valid_gen,args,parse_anchor_parameters(args.config)):\n",
    "    pass"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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