282 lines
8.0 KiB
Plaintext
282 lines
8.0 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 33,
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"id": "66ee10ca-9a42-4e52-a56c-3c4e8b470afa",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.254126Z",
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"start_time": "2024-06-12T14:23:49.251481Z"
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}
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},
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"outputs": [],
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"source": [
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"import os\n",
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"import cv2\n",
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"import glob\n",
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"import copy\n",
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"import json\n",
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"import shutil\n",
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"import numpy as np\n",
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"import pandas as pd\n",
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"import seaborn as sns\n",
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"import matplotlib.pyplot as plt\n",
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"\n",
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"from PIL import Image\n",
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"from labelme import utils\n",
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"from skimage.feature import peak_local_max"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 34,
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"id": "40711569-6f55-49d2-8a88-152c7b677218",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.257883Z",
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"start_time": "2024-06-12T14:23:49.254932Z"
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}
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},
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"outputs": [],
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"source": [
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"class_dict = {\n",
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" 1: 'Norm', \n",
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" 2: 'SV',\n",
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" 3: 'LineSV',\n",
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"}\n",
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"\n",
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"class_dict_rev = {\n",
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" 'Norm': 1, \n",
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" 'SV': 2,\n",
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" 'LineSV': 3,\n",
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"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 35,
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"id": "1762751c-7d19-482c-96ff-477b9ea50e5b",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.264837Z",
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"start_time": "2024-06-12T14:23:49.258668Z"
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}
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},
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"outputs": [],
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"source": [
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"def crop_slide(img_path, save_path, patch_size=256, step=128):\n",
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" base_name = img_path.split('/')[-1].split('.')[0]\n",
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" json_path = img_path.replace('.jpg', '.json')\n",
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" img = cv2.imread(img_path, 0)\n",
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" # img = cv2.equalizeHist(img)\n",
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" # img = cv2.GaussianBlur(img, (5, 5), 0)\n",
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" h, w = img.shape\n",
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" \n",
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" with open(json_path) as f:\n",
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" json_data = json.load(f)\n",
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"\n",
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" points = np.array([item['points'][0][::-1] for item in json_data['shapes']], np.int32)\n",
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" labels = np.array([class_dict_rev[item['label']] for item in json_data['shapes']], np.int32)\n",
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" \n",
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" mask = np.zeros_like(img)\n",
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" mask[points[:, 0], points[:, 1]] = labels\n",
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"\n",
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" for i in range(0, h-patch_size+1, step):\n",
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" for j in range(0, w-patch_size+1, step):\n",
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" v_nums = np.sum(mask[i:i+patch_size, j:j+patch_size] > 1)\n",
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" \n",
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" Image.fromarray(img[i:i+patch_size, j:j+patch_size]).save(\n",
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" os.path.join(save_path, 'img', '{}_{}_{}_{}.png'.format(base_name, str(i), str(j), str(v_nums)))\n",
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" )\n",
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" \n",
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" Image.fromarray(mask[i:i+patch_size, j:j+patch_size]).save(\n",
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" os.path.join(save_path, 'lbl', '{}_{}_{}_{}.png'.format(base_name, str(i), str(j), str(v_nums)))\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"id": "1417b046-4e1c-4b9c-9aff-cf5295701601",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.268959Z",
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"start_time": "2024-06-12T14:23:49.265788Z"
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}
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},
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"outputs": [],
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"source": [
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"def process_slide(img_path, save_path):\n",
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" base_name = img_path.split('/')[-1].split('.')[0]\n",
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" json_path = img_path.replace('.jpg', '.json')\n",
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" img = cv2.imread(img_path, 0)\n",
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" # img = cv2.equalizeHist(img)\n",
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" # img = cv2.GaussianBlur(img, (5, 5), 0)\n",
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" \n",
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" h, w = img.shape\n",
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" \n",
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" with open(json_path) as f:\n",
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" json_data = json.load(f)\n",
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"\n",
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" points = np.array([item['points'][0][::-1] for item in json_data['shapes']], np.int32)\n",
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" labels = np.array([class_dict_rev[item['label']] for item in json_data['shapes']], np.int32)\n",
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" \n",
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" # mask = np.zeros_like(img)\n",
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" # for idx, point in enumerate(points):\n",
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" # cv2.circle(mask, point[::-1], 8, int(labels[idx]), -1)\n",
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" \n",
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" mask = np.zeros_like(img)\n",
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" mask[points[:, 0], points[:, 1]] = labels\n",
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" \n",
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" Image.fromarray(img).save(\n",
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" os.path.join(save_path, 'img', '{}.png'.format(base_name))\n",
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" )\n",
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" \n",
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" Image.fromarray(mask).save(\n",
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" os.path.join(save_path, 'lbl', '{}.png'.format(base_name))\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 37,
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"id": "59c532e0-39ec-406c-8d77-e0a17a9181cd",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.273838Z",
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"start_time": "2024-06-12T14:23:49.269580Z"
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}
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},
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"outputs": [
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{
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"data": {
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"text/plain": "10"
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},
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"execution_count": 37,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"img_lst = glob.glob('../../data/linesv/slide/*.jpg') \n",
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"img_lst.sort(); len(img_lst)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 38,
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"id": "41c0bdb9-f5ca-4744-bc8a-d5d9723716c9",
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"metadata": {
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"tags": [],
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.289986Z",
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"start_time": "2024-06-12T14:23:49.288204Z"
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}
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},
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"outputs": [],
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"source": [
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"# for _type in ['train', 'valid', 'test']: \n",
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" # os.makedirs('../../data/linesv/patch_unet/{}/img'.format(_type), exist_ok=True)\n",
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" # os.makedirs('../../data/linesv/patch_unet/{}/lbl'.format(_type), exist_ok=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 39,
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"id": "378409b3-66b2-4325-8822-104c9c2519a1",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:49.293582Z",
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"start_time": "2024-06-12T14:23:49.290907Z"
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}
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},
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"outputs": [],
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"source": [
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"# crop_slide('../../data/linesv/slide/0.jpg', save_path='../../data/linesv/patch_unet/train/', step=64)\n",
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"# crop_slide('../../data/linesv/slide/3.jpg', save_path='../../data/linesv/patch_unet/valid/', step=256)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"id": "14d437d6-a43c-4471-a5ff-5df43e273819",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:52.197491Z",
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"start_time": "2024-06-12T14:23:49.294248Z"
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}
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},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"/home/gao/mouclear/cc/data/linesv/slide/2.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/4.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/6.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/8.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/10.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/20.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/30.jpg\n",
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"/home/gao/mouclear/cc/data/linesv/slide/40.jpg\n"
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]
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}
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],
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"source": [
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"for name in [2, 4, 6, 8, 10, 20, 30, 40]:\n",
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" file = '/home/gao/mouclear/cc/data/linesv/slide/{}.jpg'.format(name)\n",
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" print(file)\n",
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" process_slide(file, save_path='../../data/linesv/patch_unet/test/')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"id": "ecdb4f79-cfa5-4511-bf67-21bbe26ba403",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:52.199732Z",
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"start_time": "2024-06-12T14:23:52.198483Z"
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}
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 40,
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"id": "ee0f80af-0c81-43fc-b879-002ad63413e8",
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"metadata": {
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"ExecuteTime": {
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"end_time": "2024-06-12T14:23:52.201362Z",
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"start_time": "2024-06-12T14:23:52.200258Z"
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}
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},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"name": "python3",
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"language": "python",
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"display_name": "Python 3 (ipykernel)"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.16"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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