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{
"cells": [
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [],
"source": [
"# defining inference parameters\n",
"model_path = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\model\" # path to Layoutlmv3 model\n",
"imag_path = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\predictions\\imgs\" # images folder"
]
},
{
"cell_type": "code",
"execution_count": 33,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"^C\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"2023-12-16 02:35:50.587274: I tensorflow/core/util/port.cc:113] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
"WARNING:tensorflow:From C:\\Users\\Ayoo\\AppData\\Roaming\\Python\\Python311\\site-packages\\keras\\src\\losses.py:2976: The name tf.losses.sparse_softmax_cross_entropy is deprecated. Please use tf.compat.v1.losses.sparse_softmax_cross_entropy instead.\n",
"\n",
"c:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\site-packages\\transformers\\modeling_utils.py:881: FutureWarning: The `device` argument is deprecated and will be removed in v5 of Transformers.\n",
" warnings.warn(\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"Preparing for Inference\n",
"Starting\n",
"Preprocessing\n",
"Preprocessing done. Running OCR\n",
"JSON file saved\n",
"OCR done\n",
"Run Done\n",
"Cleaned Tesseract output done\n",
"Word list done\n",
"Box list done\n",
"Prepared for Inference Batch\n",
"Running Flattened Output\n",
"Ready for Annotation\n",
"Annotating Images\n"
]
}
],
"source": [
"! python predictions\\inference\\run_inference.py --model_path {model_path} --images_path {imag_path}"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Looking for C:\\Users\\Ayoo\\.keras-ocr\\craft_mlt_25k.h5\n"
]
},
{
"ename": "KeyboardInterrupt",
"evalue": "",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[20], line 2\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mkeras_ocr\u001b[39;00m\n\u001b[1;32m----> 2\u001b[0m pipeline\u001b[38;5;241m=\u001b[39m\u001b[43mkeras_ocr\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mpipeline\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPipeline\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\site-packages\\keras_ocr\\pipeline.py:20\u001b[0m, in \u001b[0;36mPipeline.__init__\u001b[1;34m(self, detector, recognizer, scale, max_size)\u001b[0m\n\u001b[0;32m 18\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, detector\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, recognizer\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m, scale\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2\u001b[39m, max_size\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2048\u001b[39m):\n\u001b[0;32m 19\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m detector \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m---> 20\u001b[0m detector \u001b[38;5;241m=\u001b[39m \u001b[43mdetection\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mDetector\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 21\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m recognizer \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 22\u001b[0m recognizer \u001b[38;5;241m=\u001b[39m recognition\u001b[38;5;241m.\u001b[39mRecognizer()\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\site-packages\\keras_ocr\\detection.py:686\u001b[0m, in \u001b[0;36mDetector.__init__\u001b[1;34m(self, weights, load_from_torch, optimizer, backbone_name)\u001b[0m\n\u001b[0;32m 682\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m (\n\u001b[0;32m 683\u001b[0m pretrained_key \u001b[38;5;129;01min\u001b[39;00m PRETRAINED_WEIGHTS\n\u001b[0;32m 684\u001b[0m ), \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mSelected weights configuration not found.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 685\u001b[0m weights_config \u001b[38;5;241m=\u001b[39m PRETRAINED_WEIGHTS[pretrained_key]\n\u001b[1;32m--> 686\u001b[0m weights_path \u001b[38;5;241m=\u001b[39m \u001b[43mtools\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdownload_and_verify\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 687\u001b[0m \u001b[43m \u001b[49m\u001b[43murl\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights_config\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43murl\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 688\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights_config\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mfilename\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 689\u001b[0m \u001b[43m \u001b[49m\u001b[43msha256\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mweights_config\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43msha256\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 690\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 691\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m 692\u001b[0m weights_path \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\site-packages\\keras_ocr\\tools.py:527\u001b[0m, in \u001b[0;36mdownload_and_verify\u001b[1;34m(url, sha256, cache_dir, verbose, filename)\u001b[0m\n\u001b[0;32m 525\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDownloading \u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m filepath)\n\u001b[0;32m 526\u001b[0m urllib\u001b[38;5;241m.\u001b[39mrequest\u001b[38;5;241m.\u001b[39murlretrieve(url, filepath)\n\u001b[1;32m--> 527\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m sha256 \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mor\u001b[39;00m sha256 \u001b[38;5;241m==\u001b[39m \u001b[43msha256sum\u001b[49m\u001b[43m(\u001b[49m\n\u001b[0;32m 528\u001b[0m \u001b[43m \u001b[49m\u001b[43mfilepath\u001b[49m\n\u001b[0;32m 529\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError occurred verifying sha256.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m 530\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m filepath\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\site-packages\\keras_ocr\\tools.py:491\u001b[0m, in \u001b[0;36msha256sum\u001b[1;34m(filename)\u001b[0m\n\u001b[0;32m 489\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mopen\u001b[39m(filename, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrb\u001b[39m\u001b[38;5;124m\"\u001b[39m, buffering\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m0\u001b[39m) \u001b[38;5;28;01mas\u001b[39;00m f:\n\u001b[0;32m 490\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m n \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28miter\u001b[39m(\u001b[38;5;28;01mlambda\u001b[39;00m: f\u001b[38;5;241m.\u001b[39mreadinto(mv), \u001b[38;5;241m0\u001b[39m): \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m--> 491\u001b[0m h\u001b[38;5;241m.\u001b[39mupdate(mv[:n])\n\u001b[0;32m 492\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m h\u001b[38;5;241m.\u001b[39mhexdigest()\n",
"\u001b[1;31mKeyboardInterrupt\u001b[0m: "
]
}
],
"source": [
"import keras_ocr\n",
"pipeline=keras_ocr.pipeline.Pipeline()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"1/1 [==============================] - 34s 34s/step\n",
"7/7 [==============================] - 94s 13s/step\n"
]
},
{
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" ('pp',\n",
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" ('fes',\n",
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" ('this',\n",
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" ('official',\n",
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]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"pipeline.recognize([r\"temp\\20230508_122035_preprocessed.png\"])"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Requirement already satisfied: requests in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (2.31.0)\n",
"Requirement already satisfied: charset-normalizer<4,>=2 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (3.2.0)\n",
"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (3.4)\n",
"Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (1.26.16)\n",
"Requirement already satisfied: certifi>=2017.4.17 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (2023.7.22)\n"
]
}
],
"source": [
"!pip install requests"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
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2214.0, 'Height': 42.0, 'Width': 94.0}], 'MaxHeight': 42.0, 'MinTop': 2214.0}, {'LineText': 'TIN: 000-390-189-000', 'Words': [{'WordText': 'TIN', 'Left': 13.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 90.0}, {'WordText': ':', 'Left': 13.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 90.0}, {'WordText': '000', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '-', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '390', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '-', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '189', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '-', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}, {'WordText': '000', 'Left': 109.0, 'Top': 2266.0, 'Height': 46.0, 'Width': 331.0}], 'MaxHeight': 46.0, 'MinTop': 2266.0}, {'LineText': 'BIR ACCI #', 'Words': [{'WordText': 'BIR', 'Left': 10.0, 'Top': 2318.0, 'Height': 39.0, 'Width': 78.0}, {'WordText': 'ACCI', 'Left': 93.0, 'Top': 2318.0, 'Height': 39.0, 'Width': 98.0}, {'WordText': '#', 'Left': 195.0, 'Top': 2318.0, 'Height': 39.0, 'Width': 30.0}], 'MaxHeight': 40.0, 'MinTop': 2318.0}, {'LineText': '116-000390189-000346 19602', 'Words': [{'WordText': '116', 'Left': 33.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 430.0}, {'WordText': '-', 'Left': 33.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 430.0}, {'WordText': '000390189', 'Left': 33.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 430.0}, {'WordText': '-', 'Left': 33.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 430.0}, {'WordText': '000346', 'Left': 33.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 430.0}, {'WordText': '19602', 'Left': 468.0, 'Top': 2366.0, 'Height': 43.0, 'Width': 118.0}], 'MaxHeight': 43.0, 'MinTop': 2366.0}, {'LineText': 'AcciDate: 08/01/2020', 'Words': [{'WordText': 'AcciDate', 'Left': 13.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 194.0}, {'WordText': ':', 'Left': 13.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 194.0}, {'WordText': '08', 'Left': 212.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 266.0}, {'WordText': '/', 'Left': 213.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 266.0}, {'WordText': '01', 'Left': 212.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 266.0}, {'WordText': '/', 'Left': 213.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 266.0}, {'WordText': '2020', 'Left': 212.0, 'Top': 2419.0, 'Height': 42.0, 'Width': 266.0}], 'MaxHeight': 42.0, 'MinTop': 2419.0}, {'LineText': '07/31/2025', 'Words': [{'WordText': '07', 'Left': 29.0, 'Top': 2470.0, 'Height': 44.0, 'Width': 219.0}, {'WordText': '/', 'Left': 29.0, 'Top': 2470.0, 'Height': 44.0, 'Width': 219.0}, {'WordText': '31', 'Left': 29.0, 'Top': 2470.0, 'Height': 44.0, 'Width': 219.0}, {'WordText': '/', 'Left': 29.0, 'Top': 2470.0, 'Height': 44.0, 'Width': 219.0}, {'WordText': '2025', 'Left': 29.0, 'Top': 2470.0, 'Height': 44.0, 'Width': 219.0}], 'MaxHeight': 44.0, 'MinTop': 2470.0}, {'LineText': 'Permit #:', 'Words': [{'WordText': 'Permit', 'Left': 10.0, 'Top': 2526.0, 'Height': 40.0, 'Width': 142.0}, {'WordText': '#:', 'Left': 156.0, 'Top': 2527.0, 'Height': 39.0, 'Width': 46.0}], 'MaxHeight': 40.0, 'MinTop': 2526.0}, {'LineText': 'FP112018-074-0194656-00002', 'Words': [{'WordText': 'FP112018', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '-', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '074', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '-', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '0194656', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '-', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}, {'WordText': '00002', 'Left': 33.0, 'Top': 2572.0, 'Height': 39.0, 'Width': 554.0}], 'MaxHeight': 39.0, 'MinTop': 2572.0}, {'LineText': 'Get a chance to win a trip for', 'Words': [{'WordText': 'Get', 'Left': 29.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 78.0}, {'WordText': 'a', 'Left': 112.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 34.0}, {'WordText': 'chance', 'Left': 151.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 146.0}, {'WordText': 'to', 'Left': 302.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 54.0}, {'WordText': 'win', 'Left': 361.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 83.0}, {'WordText': 'a', 'Left': 448.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 34.0}, {'WordText': 'trip', 'Left': 487.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 107.0}, {'WordText': 'for', 'Left': 599.0, 'Top': 2679.0, 'Height': 39.0, 'Width': 69.0}], 'MaxHeight': 39.0, 'MinTop': 2679.0}, {'LineText': '2 to Korea when you buy PISO', 'Words': [{'WordText': '2', 'Left': 52.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 34.0}, {'WordText': 'to', 'Left': 91.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 58.0}, {'WordText': 'Korea', 'Left': 154.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 122.0}, {'WordText': 'when', 'Left': 281.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 102.0}, {'WordText': 'you', 'Left': 388.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 78.0}, {'WordText': 'buy', 'Left': 471.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 78.0}, {'WordText': 'PISO', 'Left': 554.0, 'Top': 2731.0, 'Height': 39.0, 'Width': 91.0}], 'MaxHeight': 39.0, 'MinTop': 2731.0}, {'LineText': 'worth of 7-Eleven items. Earn', 'Words': [{'WordText': 'worth', 'Left': 29.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 116.0}, {'WordText': 'of', 'Left': 152.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 61.0}, {'WordText': '7', 'Left': 219.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 184.0}, {'WordText': '-', 'Left': 219.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 184.0}, {'WordText': 'Eleven', 'Left': 219.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 184.0}, {'WordText': 'items', 'Left': 409.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 135.0}, {'WordText': '.', 'Left': 409.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 135.0}, {'WordText': 'Earn', 'Left': 550.0, 'Top': 2783.0, 'Height': 49.0, 'Width': 99.0}], 'MaxHeight': 49.0, 'MinTop': 2783.0}, {'LineText': '3 eRaffle entries when you buy', 'Words': [{'WordText': '3', 'Left': 29.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 34.0}, {'WordText': 'eRaffle', 'Left': 68.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 166.0}, {'WordText': 'entries', 'Left': 239.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 161.0}, {'WordText': 'when', 'Left': 404.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 102.0}, {'WordText': 'you', 'Left': 512.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 78.0}, {'WordText': 'buy', 'Left': 594.0, 'Top': 2832.0, 'Height': 39.0, 'Width': 70.0}], 'MaxHeight': 39.0, 'MinTop': 2832.0}, {'LineText': 'discounted booster Items. Per', 'Words': [{'WordText': 'discounted', 'Left': 33.0, 'Top': 2888.0, 'Height': 42.0, 'Width': 221.0}, {'WordText': 'booster', 'Left': 259.0, 'Top': 2888.0, 'Height': 42.0, 'Width': 168.0}, {'WordText': 'Items', 'Left': 432.0, 'Top': 2888.0, 'Height': 42.0, 'Width': 137.0}, {'WordText': '.', 'Left': 432.0, 'Top': 2888.0, 'Height': 42.0, 'Width': 137.0}, {'WordText': 'Per', 'Left': 574.0, 'Top': 2888.0, 'Height': 42.0, 'Width': 68.0}], 'MaxHeight': 42.0, 'MinTop': 2888.0}, {'LineText': 'DTI FAIR TRADE Permit Number:', 'Words': [{'WordText': 'DTI', 'Left': 29.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 78.0}, {'WordText': 'FAIR', 'Left': 113.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 100.0}, {'WordText': 'TRADE', 'Left': 218.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 121.0}, {'WordText': 'Permit', 'Left': 344.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 142.0}, {'WordText': 'Number', 'Left': 491.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 151.0}, {'WordText': ':', 'Left': 491.0, 'Top': 2933.0, 'Height': 42.0, 'Width': 151.0}], 'MaxHeight': 42.0, 'MinTop': 2933.0}, {'LineText': '163019 Series of 2023..', 'Words': [{'WordText': '163019', 'Left': 117.0, 'Top': 2988.0, 'Height': 40.0, 'Width': 135.0}, {'WordText': 'Series', 'Left': 257.0, 'Top': 2988.0, 'Height': 40.0, 'Width': 145.0}, {'WordText': 'of', 'Left': 407.0, 'Top': 2988.0, 'Height': 40.0, 'Width': 55.0}, {'WordText': '2023', 'Left': 467.0, 'Top': 2988.0, 'Height': 40.0, 'Width': 165.0}, {'WordText': '..', 'Left': 467.0, 'Top': 2988.0, 'Height': 40.0, 'Width': 165.0}], 'MaxHeight': 40.0, 'MinTop': 2988.0}, {'LineText': 'facebook.com/711philippines.', 'Words': [{'WordText': 'facebook.com', 'Left': 52.0, 'Top': 3037.0, 'Height': 42.0, 'Width': 590.0}, {'WordText': '/', 'Left': 52.0, 'Top': 3037.0, 'Height': 42.0, 'Width': 590.0}, {'WordText': '711philippines', 'Left': 52.0, 'Top': 3037.0, 'Height': 42.0, 'Width': 590.0}, {'WordText': '.', 'Left': 52.0, 'Top': 3037.0, 'Height': 42.0, 'Width': 590.0}], 'MaxHeight': 42.0, 'MinTop': 3037.0}, {'LineText': '- THIS IS AN OFFICIAL RECEIPT -', 'Words': [{'WordText': '-', 'Left': 0.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 46.0}, {'WordText': 'THIS', 'Left': 52.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 98.0}, {'WordText': 'IS', 'Left': 155.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 57.0}, {'WordText': 'AN', 'Left': 219.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 52.0}, {'WordText': 'OFFICIAL', 'Left': 276.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 184.0}, {'WordText': 'RECEIPT', 'Left': 466.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 167.0}, {'WordText': '-', 'Left': 638.0, 'Top': 3138.0, 'Height': 46.0, 'Width': 30.0}], 'MaxHeight': 46.0, 'MinTop': 3138.0}], 'HasOverlay': True}, 'TextOrientation': '0', 'FileParseExitCode': 1, 'ParsedText': '7-ELEVEN.\\nNHJ Convenience Store\\nOwned & Operated by: Nancy A.\\nClimacosa\\nVATREGTIN #933-598-685-002\\nPoblacion, Leon, Iloilo,\\nPhilippines\\nlel #: NULL\\n05/01/2023 (Mon) 23:00:57\\nRCPT #2481347\\nROPT CNTHO\\nSTORE#3058\\nSN# :XTI43170\\nMIN #: 18112011091411051\\nSTAFF: Angelica Duante\\n7FKoreanßun\\nNissinYaSaBeet77g\\nBBHOTDOGCREMYCHEES\\n39.00 Х 6\\nchocvron? in1Ch020g\\n15.00 X\\n2\\n55.004\\n40.000\\n234.000\\n30.000\\nTotal (10)\\nCASH\\nCHANGE\\n359.00\\n1000.00\\n641.00\\nVATable\\nVAT_Tax\\nZero_Rated\\nVAT_Exempted\\n320.54\\n38.46\\n0.00\\n0.00\\nSold To: 9906087698684\\nName:\\nAddress:\\nTIN:\\nPhilippine Seven Corporation\\n7th Floor The Columbia Tower\\nOrtigas Avenue, Mandaluyong\\nCity\\nTIN: 000-390-189-000\\nBIR ACCI #\\n116-000390189-000346 19602\\nAcciDate: 08/01/2020\\n07/31/2025\\nPermit #:\\nFP112018-074-0194656-00002\\nGet a chance to win a trip for\\n2 to Korea when you buy PISO\\nworth of 7-Eleven items. Earn\\n3 eRaffle entries when you buy\\ndiscounted booster Items. Per\\nDTI FAIR TRADE Permit Number:\\n163019 Series of 2023..\\nfacebook.com/711philippines.\\n- THIS IS AN OFFICIAL RECEIPT -', 'ErrorMessage': '', 'ErrorDetails': ''}], 'OCRExitCode': 1, 'IsErroredOnProcessing': False, 'ProcessingTimeInMilliseconds': '2593', 'SearchablePDFURL': 'Searchable PDF not generated as it was not requested.'}\n"
]
}
],
"source": [
"# Import requests library\n",
"import requests\n",
"\n",
"# Define the OCR API endpoint\n",
"url = \"https://api.ocr.space/parse/image\"\n",
"\n",
"# Define the API key and the language\n",
"api_key = \"K88232854988957\"\n",
"language = \"eng\"\n",
"\n",
"# Define the image file path\n",
"image_file = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\predictions\\imgs\\20230508_122035.jpg\"\n",
"\n",
"# Open the image file as binary\n",
"with open(image_file, \"rb\") as f:\n",
" # Define the payload for the API request\n",
" payload = {\n",
" \"apikey\": api_key,\n",
" \"language\": language,\n",
" \"isOverlayRequired\": True, # Optional, set to True if you want the coordinates of the words\n",
" \"OCREngine\": 2 # OCR Engine 2 for Layoutlmv3\n",
" }\n",
" # Define the file parameter for the API request\n",
" file = {\n",
" \"file\": f\n",
" }\n",
" # Send the POST request to the OCR API\n",
" response = requests.post(url, data=payload, files=file)\n",
"\n",
"# Check the status code of the response\n",
"if response.status_code == 200:\n",
" # Parse the JSON response\n",
" result = response.json()\n",
" # Print the parsed text\n",
" print(result)\n",
"else:\n",
" # Print the error message\n",
" print(\"Error: \" + response.text)\n"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [
{
"ename": "TypeError",
"evalue": "Object of type Response is not JSON serializable",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
"Cell \u001b[1;32mIn[13], line 4\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;28;01mimport\u001b[39;00m \u001b[38;5;21;01mjson\u001b[39;00m\n\u001b[0;32m 3\u001b[0m \u001b[38;5;66;03m# Assuming 'response' is the JSON response from the OCR API\u001b[39;00m\n\u001b[1;32m----> 4\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mjson\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdumps\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresponse\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m4\u001b[39;49m\u001b[43m)\u001b[49m)\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\json\\__init__.py:238\u001b[0m, in \u001b[0;36mdumps\u001b[1;34m(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)\u001b[0m\n\u001b[0;32m 232\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m 233\u001b[0m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONEncoder\n\u001b[0;32m 234\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\n\u001b[0;32m 235\u001b[0m \u001b[43m \u001b[49m\u001b[43mskipkeys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mskipkeys\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mensure_ascii\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mensure_ascii\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 236\u001b[0m \u001b[43m \u001b[49m\u001b[43mcheck_circular\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcheck_circular\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mallow_nan\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mallow_nan\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindent\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mindent\u001b[49m\u001b[43m,\u001b[49m\n\u001b[0;32m 237\u001b[0m \u001b[43m \u001b[49m\u001b[43mseparators\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mseparators\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdefault\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdefault\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msort_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msort_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m--> 238\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkw\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mobj\u001b[49m\u001b[43m)\u001b[49m\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\json\\encoder.py:202\u001b[0m, in \u001b[0;36mJSONEncoder.encode\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 200\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39miterencode(o, _one_shot\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m 201\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(chunks, (\u001b[38;5;28mlist\u001b[39m, \u001b[38;5;28mtuple\u001b[39m)):\n\u001b[1;32m--> 202\u001b[0m chunks \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(chunks)\n\u001b[0;32m 203\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(chunks)\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\json\\encoder.py:439\u001b[0m, in \u001b[0;36m_make_iterencode.<locals>._iterencode\u001b[1;34m(o, _current_indent_level)\u001b[0m\n\u001b[0;32m 437\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mValueError\u001b[39;00m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCircular reference detected\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[0;32m 438\u001b[0m markers[markerid] \u001b[38;5;241m=\u001b[39m o\n\u001b[1;32m--> 439\u001b[0m o \u001b[38;5;241m=\u001b[39m \u001b[43m_default\u001b[49m\u001b[43m(\u001b[49m\u001b[43mo\u001b[49m\u001b[43m)\u001b[49m\n\u001b[0;32m 440\u001b[0m \u001b[38;5;28;01myield from\u001b[39;00m _iterencode(o, _current_indent_level)\n\u001b[0;32m 441\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m markers \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n",
"File \u001b[1;32mc:\\Users\\Ayoo\\anaconda3\\envs\\mlenv\\Lib\\json\\encoder.py:180\u001b[0m, in \u001b[0;36mJSONEncoder.default\u001b[1;34m(self, o)\u001b[0m\n\u001b[0;32m 161\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdefault\u001b[39m(\u001b[38;5;28mself\u001b[39m, o):\n\u001b[0;32m 162\u001b[0m \u001b[38;5;250m \u001b[39m\u001b[38;5;124;03m\"\"\"Implement this method in a subclass such that it returns\u001b[39;00m\n\u001b[0;32m 163\u001b[0m \u001b[38;5;124;03m a serializable object for ``o``, or calls the base implementation\u001b[39;00m\n\u001b[0;32m 164\u001b[0m \u001b[38;5;124;03m (to raise a ``TypeError``).\u001b[39;00m\n\u001b[1;32m (...)\u001b[0m\n\u001b[0;32m 178\u001b[0m \n\u001b[0;32m 179\u001b[0m \u001b[38;5;124;03m \"\"\"\u001b[39;00m\n\u001b[1;32m--> 180\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mObject of type \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mo\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__class__\u001b[39m\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[0;32m 181\u001b[0m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mis not JSON serializable\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
"\u001b[1;31mTypeError\u001b[0m: Object of type Response is not JSON serializable"
]
}
],
"source": [
"import json\n",
"\n",
"# Assuming 'response' is the JSON response from the OCR API\n",
"print(json.dumps(response, indent=4))\n"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "mlenv",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.11.5"
}
},
"nbformat": 4,
"nbformat_minor": 2
}
|