128 lines
2.7 KiB
Plaintext
Executable File
128 lines
2.7 KiB
Plaintext
Executable File
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 5,
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"id": "0451eb90-6a57-40b5-836d-153b4f1d08f1",
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"metadata": {},
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"outputs": [],
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"source": [
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"import cv2\n",
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"import json\n",
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"import glob\n",
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"import numpy as np\n",
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"import pandas as pd\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 utils.pesudo import load_data, get_y_3"
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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": 2,
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"id": "90798480-e2e7-4b9f-8d45-25339df1ee0d",
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"metadata": {},
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"outputs": [],
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"source": [
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"_dict = {\n",
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" 0: 'Norm',\n",
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" 1: 'LineSV',\n",
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" 2: 'SV'\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": 3,
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"id": "d1ee59e7-b42f-488c-86ab-452071f35ca9",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"0"
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]
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},
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"execution_count": 3,
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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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"json_lst = glob.glob('./03/raw/*.json', recursive=True); len(json_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": 4,
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"id": "fa258b0e-cee4-46d4-b03b-3c8e337db095",
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"metadata": {},
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"outputs": [],
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"source": [
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"thres = 160"
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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": 10,
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"id": "aafe6474-d19a-4def-963c-cb34a85b5bbd",
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"metadata": {},
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"outputs": [],
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"source": [
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"for json_path in json_lst:\n",
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" base_name = json_path.split('/')[-1]\n",
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" points, edge_index, labels, lights = load_data(json_path)\n",
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" labels = np.array([int(light < thres) for light in lights])\n",
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" labels = get_y_3(labels, edge_index)\n",
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"\n",
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" with open(json_path) as f:\n",
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" data = json.load(f)\n",
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"\n",
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" for i in range(len(data['shapes'])):\n",
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" data['shapes'][i]['label'] = _dict[labels[i]]\n",
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" \n",
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" with open('./03/{}'.format(base_name), 'w') as f:\n",
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" json.dump(data, f)"
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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": null,
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"id": "b7a319bd-9643-4eb5-83e7-09cab4925236",
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"metadata": {},
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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": null,
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"id": "53f4bd55-fad8-4447-b06f-d71aee9f2c27",
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"metadata": {},
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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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"display_name": "cmae",
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"language": "python",
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"name": "cmae"
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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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