diff --git "a/src/hybrid_clip/utils/roco_dataset.ipynb" "b/src/hybrid_clip/utils/roco_dataset.ipynb" --- "a/src/hybrid_clip/utils/roco_dataset.ipynb" +++ "b/src/hybrid_clip/utils/roco_dataset.ipynb" @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 6, "source": [ "import json\n", "import os\n", @@ -14,7 +14,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 1, "source": [ "train_path = '/home/kaumad/roco-dataset/train'\n", "train_img_dir = os.path.join(train_path, 'radiology', 'images')" @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 2, "source": [ "val_path = '/home/kaumad/roco-dataset/validation'\n", "val_img_dir = os.path.join(val_path, 'radiology', 'images')" @@ -34,7 +34,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 41, "source": [ "import torchvision\n", "\n", @@ -66,16 +66,32 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 3, + "source": [ + "def has_unicode(text):\n", + " for c in text:\n", + " if ord(c)>127:\n", + " print(f\"unicode: {c}\", text)\n", + " return True\n", + " return False" + ], + "outputs": [], + "metadata": {} + }, + { + "cell_type": "code", + "execution_count": 4, "source": [ "import collections\n", "\n", + "lens = []\n", "\n", - "def read_lines(img_dir, csv_file):\n", + "def read_lines(img_dir, csv_file, n_lines=0):\n", " lines = []\n", " image_path_to_caption = collections.defaultdict(list)\n", " for idx, row in csv_file.iterrows():\n", - "\n", + " if n_lines > 0 and idx > n_lines:\n", + " break\n", " img_path = os.path.join(img_dir, row['name'])\n", " if not os.path.exists(img_path):\n", " continue\n", @@ -87,8 +103,18 @@ " # TODO check if the image is not empty\n", " caption = row['caption'].lower().rstrip().replace(\n", " \"\\\\n\", \"\").rstrip(\".\")\n", + " try:\n", + " caption = caption.encode('ascii')\n", + " except:\n", + " continue\n", + " \n", + " lens.append(len(caption))\n", + " \n", + " if len(caption) < 10:\n", + " continue\n", " # caption = caption.replace(\"\\\\n\", \"\").rstrip()\n", " # print([caption])\n", + " # has_unicode(caption)\n", " caption = f\"{caption}\"\n", " image_path_to_caption[img_path].append(caption)\n", "\n", @@ -103,17 +129,10156 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 7, "source": [ "train_csv = pd.read_csv(os.path.join(train_path, 'radiology', 'traindata.csv'))\n", - "lines = read_lines(train_img_dir, train_csv)" + "lines = read_lines(train_img_dir, train_csv, n_lines=0)" ], "outputs": [ { "output_type": "stream", "name": "stdout", "text": [ - "/home/kaumad/roco-dataset/train/radiology/images/PMC4240561_MA-68-291-g002.jpg\n" + "/home/kaumad/roco-dataset/train/radiology/images/PMC4083729_AMHSR-4-14-g002.jpg\n", + "/home/kaumad/roco-dataset/train/radiology/images/PMC2837471_IJD2009-150251.001.jpg\n", + 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"/home/kaumad/roco-dataset/train/radiology/images/PMC5024848_AJUM-12-10-g010.jpg\n", + "/home/kaumad/roco-dataset/train/radiology/images/PMC5576157_gr4.jpg\n", + "/home/kaumad/roco-dataset/train/radiology/images/PMC4772905_ccrep-9-2016-011f1.jpg\n" ] } ], @@ -121,53 +10286,43 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 56, "source": [ - "json_dir = '../../../data'\n", - "with open(os.path.join(json_dir, \"train_dataset.json\"), \"w\") as f:\n", - " f.write(\"\\n\".join(lines))" + "import numpy as np\n", + "lens = np.array(lens)" ], "outputs": [], "metadata": {} }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 46, "source": [ - "val_csv = pd.read_csv(os.path.join(val_path, 'radiology', 'valdata.csv'))\n", - "lines = read_lines(val_img_dir, val_csv)" + "json_dir = '../../../data'\n", + "with open(os.path.join(json_dir, \"train_dataset.json\"), \"w\") as f:\n", + " f.write(\"\\n\".join(lines))" ], "outputs": [], "metadata": {} }, { "cell_type": "code", - "execution_count": null, + "execution_count": 48, "source": [ - "with open(os.path.join(json_dir, \"valid_dataset.json\"), \"w\") as f:\n", - " f.write(\"\\n\".join(lines))" + "val_csv = pd.read_csv(os.path.join(val_path, 'radiology', 'valdata.csv'))\n", + "lines = read_lines(val_img_dir, val_csv, n_lines=0)" ], "outputs": [], "metadata": {} }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 49, "source": [ - "lines[0]" - ], - "outputs": [ - { - "output_type": "execute_result", - "data": { - "text/plain": [ - "'{\"image_path\": \"/home/kaumad/roco-dataset/validation/radiology/images/PMC3970251_CRIONM2014-931546.003.jpg\", \"captions\": [\" axial computed tomography scan of the pelvis showing a diffuse infiltration of the bladder wall, catheter in situ (arrow)\"]}'" - ] - }, - "metadata": {}, - "execution_count": 16 - } + "with open(os.path.join(json_dir, \"valid_dataset-sample.json\"), \"w\") as f:\n", + " f.write(\"\\n\".join(lines))" ], + "outputs": [], "metadata": {} }, {