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Test.ipynb
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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": 89,
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"metadata": {},
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"outputs": [],
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"source": [
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"import torch \n",
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"import torch.nn as nn\n",
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"from parseq.system import System\n",
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"import yaml\n",
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"import cv2\n",
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"from parseq.augmentation import trans\n",
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"import PIL\n",
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"import imgaug\n",
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"import torchvision\n",
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"from wpodnet.lib_detection import load_model_wpod, detect_lp\n",
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"import numpy as np\n",
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"import gradio as gr \n",
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"import tensorflow as tf\n",
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"from tensorflow import keras\n",
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"import timm\n",
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"import pytorch_lightning as pl"
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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": 91,
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"metadata": {},
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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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"tensorflow==2.13.1\n",
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"torch==2.4.1+cu118\n",
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"gradio==4.44.1\n",
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"timm==1.0.9\n",
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"PIL==10.2.0\n",
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"imgaug==0.4.0\n",
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"opencv-python==4.10.0\n",
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"torchvision==0.19.1+cu118\n"
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]
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}
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],
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"source": [
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"print(f'tensorflow=={tf.__version__}')\n",
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"print(f'torch=={torch.__version__}')\n",
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"print(f'gradio=={gr.__version__}')\n",
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"print(f'timm=={timm.__version__}')\n",
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"print(f'PIL=={PIL.__version__}')\n",
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"print(f'imgaug=={imgaug.__version__}')\n",
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"print(f'opencv-python=={cv2.__version__}')\n",
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"print(f'torchvision=={torchvision.__version__}')"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "virtual",
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"language": "python",
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"name": "python3"
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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": "3.10.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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