cleaned repo, changed api
Browse files- Layoutlmv3_inference/ocr.py +1 -2
- exp2.ipynb +0 -183
- experiment.ipynb +0 -1337
- output_folders/20240517_115717/img_display/images.png +0 -0
- output_folders/20240517_115717/img_display/receipt_19.jpg +0 -0
- output_folders/20240517_115717/img_display/sample_711.jpg +0 -0
- output_folders/20240517_115717/img_display/sample_711.jpg_inference.jpg +0 -0
- output_folders/20240517_115717/img_display/sample_coop.jpg +0 -0
- output_folders/20240517_115717/img_display/sample_coop.jpg_inference.jpg +0 -0
- output_folders/20240517_115717/inferenced/csv_files/Output_0.csv +0 -4
- output_folders/20240517_115717/inferenced/csv_files/Output_1.csv +0 -3
- output_folders/20240517_115717/inferenced/output.csv +0 -6
- output_folders/20240517_115717/labeled/Output_0.json +0 -1
- output_folders/20240517_115717/labeled/Output_1.json +0 -1
- output_folders/20240517_115717/sample_711_ocr.json +0 -1
- output_folders/20240517_115717/sample_711_preprocessed.jpg +0 -0
- output_folders/20240517_115717/sample_coop_ocr.json +0 -1
- output_folders/20240517_115717/sample_coop_preprocessed.jpg +0 -0
- output_folders/20240517_115717/uploads/receipt_19.jpg +0 -0
- output_folders/20240517_115717/uploads/sample_711.jpg +0 -0
- output_folders/20240517_115717/uploads/sample_coop.jpg +0 -0
- packages.txt +0 -1
- requirements+old.txt +0 -255
- sample_711.jpg +0 -0
- static/temp/img_display/receipt_876.jpg +0 -0
- static/temp/uploads/receipt_876.jpg +0 -0
Layoutlmv3_inference/ocr.py
CHANGED
@@ -92,8 +92,7 @@ def run_tesseract_on_preprocessed_image(preprocessed_image, image_path):
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url = "https://api.ocr.space/parse/image"
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# Define the API key and the language
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api_key = "K88232854988957"
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language = "eng"
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# Save the preprocessed image
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url = "https://api.ocr.space/parse/image"
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# Define the API key and the language
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+
api_key = os.getenv("ocr_space")
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language = "eng"
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# Save the preprocessed image
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exp2.ipynb
DELETED
@@ -1,183 +0,0 @@
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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": 1,
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"metadata": {},
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"outputs": [],
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"source": [
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"# import the necessary packages\n",
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"from imutils.perspective import four_point_transform\n",
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"import pytesseract\n",
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"import argparse\n",
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"import imutils\n",
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"import cv2\n",
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"import re"
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]
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"usage: ipykernel_launcher.py [-h] -i INPUT [-d DEBUG]\n",
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"ipykernel_launcher.py: error: the following arguments are required: -i/--input\n"
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]
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},
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{
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"ename": "SystemExit",
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"evalue": "2",
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"output_type": "error",
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"traceback": [
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"An exception has occurred, use %tb to see the full traceback.\n",
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"\u001b[1;31mSystemExit\u001b[0m\u001b[1;31m:\u001b[0m 2\n"
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]
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}
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],
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"source": [
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"input= \"sample_711.jpg\"\n",
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"\n",
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"# Construct the argument parser\n",
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"ap = argparse.ArgumentParser()\n",
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"ap.add_argument(\"-i\", \"--input\", required=True,\n",
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"\thelp=\"path to input receipt image\")\n",
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"ap.add_argument(\"-d\", \"--debug\", type=int, default=-1,\n",
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"\thelp=\"whether or not we are visualizing each step of the pipeline\")\n",
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"\n",
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"# Parse the arguments\n",
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"args = vars(ap.parse_args())\n"
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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": 14,
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"metadata": {},
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"outputs": [
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{
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"ename": "NameError",
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"evalue": "name 'args' is not defined",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mNameError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[1;32mIn[14], line 4\u001b[0m\n\u001b[0;32m 1\u001b[0m \u001b[38;5;66;03m# load the input image from disk, resize it, and compute the ratio\u001b[39;00m\n\u001b[0;32m 2\u001b[0m \u001b[38;5;66;03m# of the *new* width to the *old* width\u001b[39;00m\n\u001b[0;32m 3\u001b[0m image\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124msample_711.jpg\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m----> 4\u001b[0m orig \u001b[38;5;241m=\u001b[39m cv2\u001b[38;5;241m.\u001b[39mimread(\u001b[43margs\u001b[49m[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mimage\u001b[39m\u001b[38;5;124m\"\u001b[39m])\n\u001b[0;32m 5\u001b[0m image \u001b[38;5;241m=\u001b[39m orig\u001b[38;5;241m.\u001b[39mcopy()\n\u001b[0;32m 6\u001b[0m image \u001b[38;5;241m=\u001b[39m imutils\u001b[38;5;241m.\u001b[39mresize(image, width\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m500\u001b[39m)\n",
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"\u001b[1;31mNameError\u001b[0m: name 'args' is not defined"
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]
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}
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],
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"source": [
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"# load the input image from disk, resize it, and compute the ratio\n",
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"# of the *new* width to the *old* width\n",
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"image= \"sample_711.jpg\"\n",
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"orig = cv2.imread(args[\"image\"])\n",
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"image = orig.copy()\n",
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"image = imutils.resize(image, width=500)\n",
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"ratio = orig.shape[1] / float(image.shape[1])"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# convert the image to grayscale, blur it slightly, and then apply\n",
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"# edge detection\n",
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"gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)\n",
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"blurred = cv2.GaussianBlur(gray, (5, 5,), 0)\n",
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"edged = cv2.Canny(blurred, 75, 200)\n",
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"# check to see if we should show the output of our edge detection\n",
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"# procedure\n",
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"if args[\"debug\"] > 0:\n",
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"\tcv2.imshow(\"Input\", image)\n",
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"\tcv2.imshow(\"Edged\", edged)\n",
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"\tcv2.waitKey(0)"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# find contours in the edge map and sort them by size in descending\n",
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"# order\n",
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"cnts = cv2.findContours(edged.copy(), cv2.RETR_EXTERNAL,\n",
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"\tcv2.CHAIN_APPROX_SIMPLE)\n",
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"cnts = imutils.grab_contours(cnts)\n",
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"cnts = sorted(cnts, key=cv2.contourArea, reverse=True)"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# initialize a contour that corresponds to the receipt outline\n",
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"receiptCnt = None\n",
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"# loop over the contours\n",
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"for c in cnts:\n",
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"\t# approximate the contour\n",
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"\tperi = cv2.arcLength(c, True)\n",
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"\tapprox = cv2.approxPolyDP(c, 0.02 * peri, True)\n",
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"\t# if our approximated contour has four points, then we can\n",
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"\t# assume we have found the outline of the receipt\n",
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"\tif len(approx) == 4:\n",
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"\t\treceiptCnt = approx\n",
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"\t\tbreak\n",
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"# if the receipt contour is empty then our script could not find the\n",
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"# outline and we should be notified\n",
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"if receiptCnt is None:\n",
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"\traise Exception((\"Could not find receipt outline. \"\n",
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"\t\t\"Try debugging your edge detection and contour steps.\"))"
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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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"metadata": {},
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"outputs": [],
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"source": [
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"# check to see if we should draw the contour of the receipt on the\n",
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"# image and then display it to our screen\n",
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"if args[\"debug\"] > 0:\n",
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"\toutput = image.copy()\n",
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"\tcv2.drawContours(output, [receiptCnt], -1, (0, 255, 0), 2)\n",
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"\tcv2.imshow(\"Receipt Outline\", output)\n",
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"\tcv2.waitKey(0)\n",
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"# apply a four-point perspective transform to the *original* image to\n",
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"# obtain a top-down bird's-eye view of the receipt\n",
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"receipt = four_point_transform(orig, receiptCnt.reshape(4, 2) * ratio)\n",
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"# show transformed image\n",
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"cv2.imshow(\"Receipt Transform\", imutils.resize(receipt, width=500))\n",
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"cv2.waitKey(0)"
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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": "mlenv",
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"language": "python",
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"name": "python3"
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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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"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": "3.11.4"
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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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experiment.ipynb
DELETED
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"cells": [
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"outputs": [],
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"source": [
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"# defining inference parameters\n",
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"model_path = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\model\" # path to Layoutlmv3 model\n",
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"imag_path = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\predictions\\imgs\" # images folder"
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]
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"text": [
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"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",
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"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",
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"\n",
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"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",
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" warnings.warn(\n"
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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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"Preparing for Inference\n",
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"Starting\n",
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"Preprocessing\n",
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"Preprocessing done. Running OCR\n",
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"JSON file saved\n",
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"OCR done\n",
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"Run Done\n",
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"Cleaned Tesseract output done\n",
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"Word list done\n",
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"Box list done\n",
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"Prepared for Inference Batch\n",
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"Running Flattened Output\n",
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"Ready for Annotation\n",
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"Annotating Images\n"
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]
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}
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],
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"source": [
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"! python predictions\\inference\\run_inference.py --model_path {model_path} --images_path {imag_path}"
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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": 20,
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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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"Looking for C:\\Users\\Ayoo\\.keras-ocr\\craft_mlt_25k.h5\n"
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]
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},
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{
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"ename": "KeyboardInterrupt",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[1;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)",
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"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",
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"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",
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"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",
|
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"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",
|
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"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",
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]
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}
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],
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"source": [
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"import keras_ocr\n",
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"pipeline=keras_ocr.pipeline.Pipeline()"
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},
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{
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"cell_type": "code",
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{
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1221 |
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1222 |
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1223 |
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"Requirement already satisfied: idna<4,>=2.5 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (3.4)\n",
|
1224 |
-
"Requirement already satisfied: urllib3<3,>=1.21.1 in c:\\users\\ayoo\\anaconda3\\envs\\mlenv\\lib\\site-packages (from requests) (1.26.16)\n",
|
1225 |
-
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1226 |
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]
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1228 |
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1229 |
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1231 |
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1232 |
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1233 |
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1234 |
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'Width': 111.0}, {'WordText': ':', 'Left': 10.0, 'Top': 1856.0, 'Height': 39.0, 'Width': 111.0}], 'MaxHeight': 39.0, 'MinTop': 1856.0}, {'LineText': 'Address:', 'Words': [{'WordText': 'Address', 'Left': 13.0, 'Top': 1907.0, 'Height': 40.0, 'Width': 170.0}, {'WordText': ':', 'Left': 13.0, 'Top': 1907.0, 'Height': 40.0, 'Width': 170.0}], 'MaxHeight': 40.0, 'MinTop': 1907.0}, {'LineText': 'TIN:', 'Words': [{'WordText': 'TIN', 'Left': 13.0, 'Top': 1957.0, 'Height': 39.0, 'Width': 85.0}, {'WordText': ':', 'Left': 13.0, 'Top': 1957.0, 'Height': 39.0, 'Width': 85.0}], 'MaxHeight': 39.0, 'MinTop': 1957.0}, {'LineText': 'Philippine Seven Corporation', 'Words': [{'WordText': 'Philippine', 'Left': 10.0, 'Top': 2060.0, 'Height': 43.0, 'Width': 226.0}, {'WordText': 'Seven', 'Left': 241.0, 'Top': 2060.0, 'Height': 43.0, 'Width': 118.0}, {'WordText': 'Corporation', 'Left': 365.0, 'Top': 2060.0, 'Height': 43.0, 'Width': 241.0}], 'MaxHeight': 43.0, 'MinTop': 2060.0}, {'LineText': '7th Floor The Columbia Tower', 'Words': [{'WordText': '7th', 'Left': 13.0, 'Top': 2116.0, 'Height': 36.0, 'Width': 72.0}, {'WordText': 'Floor', 'Left': 90.0, 'Top': 2116.0, 'Height': 36.0, 'Width': 126.0}, {'WordText': 'The', 'Left': 220.0, 'Top': 2116.0, 'Height': 36.0, 'Width': 76.0}, {'WordText': 'Columbia', 'Left': 301.0, 'Top': 2116.0, 'Height': 36.0, 'Width': 189.0}, {'WordText': 'Tower', 'Left': 495.0, 'Top': 2116.0, 'Height': 36.0, 'Width': 108.0}], 'MaxHeight': 36.0, 'MinTop': 2116.0}, {'LineText': 'Ortigas Avenue, Mandaluyong', 'Words': [{'WordText': 'Ortigas', 'Left': 33.0, 'Top': 2161.0, 'Height': 49.0, 'Width': 154.0}, {'WordText': 'Avenue', 'Left': 192.0, 'Top': 2161.0, 'Height': 49.0, 'Width': 159.0}, {'WordText': ',', 'Left': 192.0, 'Top': 2161.0, 'Height': 49.0, 'Width': 159.0}, {'WordText': 'Mandaluyong', 'Left': 358.0, 'Top': 2161.0, 'Height': 49.0, 'Width': 248.0}], 'MaxHeight': 49.0, 'MinTop': 2161.0}, {'LineText': 'City', 'Words': [{'WordText': 'City', 'Left': 29.0, 'Top': 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"
|
1243 |
-
]
|
1244 |
-
}
|
1245 |
-
],
|
1246 |
-
"source": [
|
1247 |
-
"# Import requests library\n",
|
1248 |
-
"import requests\n",
|
1249 |
-
"\n",
|
1250 |
-
"# Define the OCR API endpoint\n",
|
1251 |
-
"url = \"https://api.ocr.space/parse/image\"\n",
|
1252 |
-
"\n",
|
1253 |
-
"# Define the API key and the language\n",
|
1254 |
-
"api_key = \"K88232854988957\"\n",
|
1255 |
-
"language = \"eng\"\n",
|
1256 |
-
"\n",
|
1257 |
-
"# Define the image file path\n",
|
1258 |
-
"image_file = r\"C:\\Users\\Ayoo\\Desktop\\webapp\\predictions\\imgs\\20230508_122035.jpg\"\n",
|
1259 |
-
"\n",
|
1260 |
-
"# Open the image file as binary\n",
|
1261 |
-
"with open(image_file, \"rb\") as f:\n",
|
1262 |
-
" # Define the payload for the API request\n",
|
1263 |
-
" payload = {\n",
|
1264 |
-
" \"apikey\": api_key,\n",
|
1265 |
-
" \"language\": language,\n",
|
1266 |
-
" \"isOverlayRequired\": True, # Optional, set to True if you want the coordinates of the words\n",
|
1267 |
-
" \"OCREngine\": 2 # OCR Engine 2 for Layoutlmv3\n",
|
1268 |
-
" }\n",
|
1269 |
-
" # Define the file parameter for the API request\n",
|
1270 |
-
" file = {\n",
|
1271 |
-
" \"file\": f\n",
|
1272 |
-
" }\n",
|
1273 |
-
" # Send the POST request to the OCR API\n",
|
1274 |
-
" response = requests.post(url, data=payload, files=file)\n",
|
1275 |
-
"\n",
|
1276 |
-
"# Check the status code of the response\n",
|
1277 |
-
"if response.status_code == 200:\n",
|
1278 |
-
" # Parse the JSON response\n",
|
1279 |
-
" result = response.json()\n",
|
1280 |
-
" # Print the parsed text\n",
|
1281 |
-
" print(result)\n",
|
1282 |
-
"else:\n",
|
1283 |
-
" # Print the error message\n",
|
1284 |
-
" print(\"Error: \" + response.text)\n"
|
1285 |
-
]
|
1286 |
-
},
|
1287 |
-
{
|
1288 |
-
"cell_type": "code",
|
1289 |
-
"execution_count": 13,
|
1290 |
-
"metadata": {},
|
1291 |
-
"outputs": [
|
1292 |
-
{
|
1293 |
-
"ename": "TypeError",
|
1294 |
-
"evalue": "Object of type Response is not JSON serializable",
|
1295 |
-
"output_type": "error",
|
1296 |
-
"traceback": [
|
1297 |
-
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
|
1298 |
-
"\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)",
|
1299 |
-
"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",
|
1300 |
-
"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",
|
1301 |
-
"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",
|
1302 |
-
"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",
|
1303 |
-
"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",
|
1304 |
-
"\u001b[1;31mTypeError\u001b[0m: Object of type Response is not JSON serializable"
|
1305 |
-
]
|
1306 |
-
}
|
1307 |
-
],
|
1308 |
-
"source": [
|
1309 |
-
"import json\n",
|
1310 |
-
"\n",
|
1311 |
-
"# Assuming 'response' is the JSON response from the OCR API\n",
|
1312 |
-
"print(json.dumps(response, indent=4))\n"
|
1313 |
-
]
|
1314 |
-
}
|
1315 |
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],
|
1316 |
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"metadata": {
|
1317 |
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"kernelspec": {
|
1318 |
-
"display_name": "mlenv",
|
1319 |
-
"language": "python",
|
1320 |
-
"name": "python3"
|
1321 |
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},
|
1322 |
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"language_info": {
|
1323 |
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"codemirror_mode": {
|
1324 |
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"name": "ipython",
|
1325 |
-
"version": 3
|
1326 |
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},
|
1327 |
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"file_extension": ".py",
|
1328 |
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"mimetype": "text/x-python",
|
1329 |
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"name": "python",
|
1330 |
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"nbconvert_exporter": "python",
|
1331 |
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"pygments_lexer": "ipython3",
|
1332 |
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"version": "3.11.5"
|
1333 |
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}
|
1334 |
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},
|
1335 |
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"nbformat": 4,
|
1336 |
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"nbformat_minor": 2
|
1337 |
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}
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output_folders/20240517_115717/img_display/images.png
DELETED
Binary file (9.01 kB)
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output_folders/20240517_115717/img_display/receipt_19.jpg
DELETED
Binary file (611 kB)
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output_folders/20240517_115717/img_display/sample_711.jpg
DELETED
Binary file (682 kB)
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output_folders/20240517_115717/img_display/sample_711.jpg_inference.jpg
DELETED
Binary file (301 kB)
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output_folders/20240517_115717/img_display/sample_coop.jpg
DELETED
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output_folders/20240517_115717/img_display/sample_coop.jpg_inference.jpg
DELETED
Binary file (276 kB)
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output_folders/20240517_115717/inferenced/csv_files/Output_0.csv
DELETED
@@ -1,4 +0,0 @@
|
|
1 |
-
RECEIPTNUMBER,MERCHANTNAME,MERCHANTADDRESS,TRANSACTIONDATE,TRANSACTIONTIME,ITEMS,PRICE,TOTAL,VATTAX
|
2 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,NESTEALEMICETSDOML,35.000,108,4.00 67.86
|
3 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,A,41.000,108,4.00 67.86
|
4 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,NESTEALEMICETSDOML A TaGstrabryT200ml,35.000 41.000,108,4.00 67.86
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output_folders/20240517_115717/inferenced/csv_files/Output_1.csv
DELETED
@@ -1,3 +0,0 @@
|
|
1 |
-
RECEIPTNUMBER,MERCHANTNAME,MERCHANTADDRESS,TRANSACTIONDATE,TRANSACTIONTIME,ITEMS,PRICE,TOTAL,VATTAX
|
2 |
-
000036410,BVSU Multi Purpose Cooperative,Luna Street Lapaz Iloslo City,10 - 25 - 2023,01 : 29 : 49 PM,COXE,13.00,13.00,
|
3 |
-
000036410,BVSU Multi Purpose Cooperative,Luna Street Lapaz Iloslo City,10 - 25 - 2023,01 : 29 : 49 PM,COXE 195ML,13.00,13.00,
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output_folders/20240517_115717/inferenced/output.csv
DELETED
@@ -1,6 +0,0 @@
|
|
1 |
-
RECEIPTNUMBER,MERCHANTNAME,MERCHANTADDRESS,TRANSACTIONDATE,TRANSACTIONTIME,ITEMS,PRICE,TOTAL,VATTAX
|
2 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,NESTEALEMICETSDOML,35.000,108,4.00 67.86
|
3 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,A,41.000,108,4.00 67.86
|
4 |
-
# 3058,BHu Convenience,"Poblacion , Leon , Iloila .",05 / 00 / 2023,06 : 54 : 23,NESTEALEMICETSDOML A TaGstrabryT200ml,35.000 41.000,108,4.00 67.86
|
5 |
-
000036410,BVSU Multi Purpose Cooperative,Luna Street Lapaz Iloslo City,10 - 25 - 2023,01 : 29 : 49 PM,COXE,13.00,13.00,
|
6 |
-
000036410,BVSU Multi Purpose Cooperative,Luna Street Lapaz Iloslo City,10 - 25 - 2023,01 : 29 : 49 PM,COXE 195ML,13.00,13.00,
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output_folders/20240517_115717/labeled/Output_0.json
DELETED
@@ -1 +0,0 @@
|
|
1 |
-
{"output": [{"text": "tons", "label": "MERCHANTADDRESS", "words": [{"id": 37, "box": [322.0, 624.0, 426.0, 676.0], "text": "tons"}]}, {"text": "11457229", "label": "RECEIPTNUMBER", "words": [{"id": 44, "box": [121.0, 728.0, 299.0, 773.0], "text": "11457229"}]}, {"text": "76.000", "label": "TOTAL", "words": [{"id": 71, "box": [592.0, 1134.0, 706.0, 1183.0], "text": "76.000"}]}, {"text": "108", "label": "TOTAL", "words": [{"id": 77, "box": [657.0, 1390.0, 705.0, 1436.0], "text": "108"}]}, {"text": "0.00", "label": "VATTAX", "words": [{"id": 79, "box": [611.0, 1494.0, 705.0, 1539.0], "text": "0.00"}]}, {"text": "BHu Convenience", "label": "MERCHANTNAME", "words": [{"id": 0, "box": [120.0, 208.0, 193.0, 257.0], "text": "BHu"}, {"id": 1, "box": [200.0, 208.0, 451.0, 257.0], "text": "Convenience"}]}, {"text": "Poblacion , Leon , Iloila .", "label": "MERCHANTADDRESS", "words": [{"id": 21, "box": [101.0, 416.0, 314.0, 471.0], "text": "Poblacion"}, {"id": 22, "box": [101.0, 416.0, 314.0, 471.0], "text": ","}, {"id": 23, "box": [321.0, 416.0, 445.0, 471.0], "text": "Leon"}, {"id": 24, "box": [321.0, 416.0, 445.0, 471.0], "text": ","}, {"id": 25, "box": [452.0, 416.0, 611.0, 471.0], "text": "Iloila"}, {"id": 26, "box": [452.0, 416.0, 611.0, 471.0], "text": "."}]}, {"text": "05 / 00 / 2023", "label": "TRANSACTIONDATE", "words": [{"id": 32, "box": [101.0, 624.0, 316.0, 676.0], "text": "05"}, {"id": 33, "box": [101.0, 624.0, 316.0, 676.0], "text": "/"}, {"id": 34, "box": [101.0, 624.0, 316.0, 676.0], "text": "00"}, {"id": 35, "box": [101.0, 624.0, 316.0, 676.0], "text": "/"}, {"id": 36, "box": [101.0, 624.0, 316.0, 676.0], "text": "2023"}]}, {"text": "06 : 54 : 23", "label": "TRANSACTIONTIME", "words": [{"id": 38, "box": [432.0, 624.0, 614.0, 676.0], "text": "06"}, {"id": 39, "box": [432.0, 624.0, 614.0, 676.0], "text": ":"}, {"id": 40, "box": [432.0, 624.0, 614.0, 676.0], "text": "54"}, {"id": 41, "box": [432.0, 624.0, 614.0, 676.0], "text": ":"}, {"id": 42, "box": [432.0, 624.0, 614.0, 676.0], "text": "23"}]}, {"text": "# 3058", "label": "RECEIPTNUMBER", "words": [{"id": 48, "box": [130.0, 779.0, 238.0, 822.0], "text": "#"}, {"id": 49, "box": [130.0, 779.0, 238.0, 822.0], "text": "3058"}]}, {"text": "NESTEALEMICETSDOML A TaGstrabryT200ml", "label": "ITEMS", "words": [{"id": 62, "box": [20.0, 984.0, 407.0, 1026.0], "text": "NESTEALEMICETSDOML"}, {"id": 63, "box": [23.0, 1033.0, 57.0, 1078.0], "text": "A"}, {"id": 64, "box": [62.0, 1033.0, 403.0, 1078.0], "text": "TaGstrabryT200ml"}]}, {"text": "35.000 41.000", "label": "PRICE", "words": [{"id": 65, "box": [566.0, 981.0, 703.0, 1030.0], "text": "35.000"}, {"id": 66, "box": [569.0, 1032.0, 703.0, 1078.0], "text": "41.000"}]}, {"text": "4.00 67.86", "label": "VATTAX", "words": [{"id": 73, "box": [611.0, 1241.0, 702.0, 1286.0], "text": "4.00"}, {"id": 74, "box": [591.0, 1338.0, 705.0, 1384.0], "text": "67.86"}]}]}
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output_folders/20240517_115717/labeled/Output_1.json
DELETED
@@ -1 +0,0 @@
|
|
1 |
-
{"output": [{"text": "000036410", "label": "RECEIPTNUMBER", "words": [{"id": 238, "box": [266.0, 420.0, 466.0, 464.0], "text": "000036410"}]}, {"text": "13.00", "label": "PRICE", "words": [{"id": 290, "box": [876.0, 946.0, 991.0, 992.0], "text": "13.00"}]}, {"text": "13.00", "label": "TOTAL", "words": [{"id": 292, "box": [331.0, 1100.0, 443.0, 1149.0], "text": "13.00"}]}, {"text": "BVSU Multi Purpose Cooperative", "label": "MERCHANTNAME", "words": [{"id": 204, "box": [207.0, 53.0, 299.0, 102.0], "text": "BVSU"}, {"id": 205, "box": [305.0, 53.0, 427.0, 102.0], "text": "Multi"}, {"id": 206, "box": [434.0, 53.0, 593.0, 102.0], "text": "Purpose"}, {"id": 207, "box": [599.0, 53.0, 846.0, 102.0], "text": "Cooperative"}]}, {"text": "Luna Street Lapaz Iloslo City", "label": "MERCHANTADDRESS", "words": [{"id": 208, "box": [331.0, 105.0, 435.0, 154.0], "text": "Luna"}, {"id": 209, "box": [441.0, 105.0, 588.0, 154.0], "text": "Street"}, {"id": 210, "box": [594.0, 105.0, 705.0, 154.0], "text": "Lapaz"}, {"id": 211, "box": [403.0, 158.0, 544.0, 208.0], "text": "Iloslo"}, {"id": 212, "box": [550.0, 157.0, 643.0, 207.0], "text": "City"}]}, {"text": "10 - 25 - 2023", "label": "TRANSACTIONDATE", "words": [{"id": 239, "box": [269.0, 472.0, 486.0, 520.0], "text": "10"}, {"id": 240, "box": [269.0, 472.0, 486.0, 520.0], "text": "-"}, {"id": 241, "box": [269.0, 472.0, 486.0, 520.0], "text": "25"}, {"id": 242, "box": [269.0, 472.0, 486.0, 520.0], "text": "-"}, {"id": 243, "box": [269.0, 472.0, 486.0, 520.0], "text": "2023"}]}, {"text": "COXE 195ML", "label": "ITEMS", "words": [{"id": 263, "box": [92.0, 943.0, 218.0, 986.0], "text": "COXE"}, {"id": 264, "box": [223.0, 943.0, 334.0, 986.0], "text": "195ML"}]}, {"text": "01 : 29 : 49 PM", "label": "TRANSACTIONTIME", "words": [{"id": 283, "box": [790.0, 472.0, 976.0, 520.0], "text": "01"}, {"id": 284, "box": [790.0, 472.0, 976.0, 520.0], "text": ":"}, {"id": 285, "box": [790.0, 472.0, 976.0, 520.0], "text": "29"}, {"id": 286, "box": [790.0, 472.0, 976.0, 520.0], "text": ":"}, {"id": 287, "box": [790.0, 472.0, 976.0, 520.0], "text": "49"}, {"id": 288, "box": [981.0, 472.0, 1033.0, 519.0], "text": "PM"}]}]}
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output_folders/20240517_115717/sample_711_ocr.json
DELETED
@@ -1 +0,0 @@
|
|
1 |
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Ear\n3 eRattle 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": "967", "SearchablePDFURL": "Searchable PDF not generated as it was not requested."}
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8: 000036513", "Words": [{"WordText": "Tr", "Left": 371.0, "Top": 1521.0, "Height": 46.0, "Width": 52.0}, {"WordText": "8", "Left": 429.0, "Top": 1521.0, "Height": 46.0, "Width": 46.0}, {"WordText": ":", "Left": 429.0, "Top": 1521.0, "Height": 46.0, "Width": 46.0}, {"WordText": "000036513", "Left": 480.0, "Top": 1521.0, "Height": 46.0, "Width": 192.0}], "MaxHeight": 46.0, "MinTop": 1521.0}, {"LineText": "SUPPLIER : AVAMICA COMPUTER TECHNOLOGIES", "Words": [{"WordText": "SUPPLIER", "Left": 10.0, "Top": 1623.0, "Height": 53.0, "Width": 176.0}, {"WordText": ":", "Left": 192.0, "Top": 1623.0, "Height": 52.0, "Width": 13.0}, {"WordText": "AVAMICA", "Left": 211.0, "Top": 1623.0, "Height": 52.0, "Width": 149.0}, {"WordText": "COMPUTER", "Left": 367.0, "Top": 1623.0, "Height": 52.0, "Width": 182.0}, {"WordText": "TECHNOLOGIES", "Left": 556.0, "Top": 1623.0, "Height": 53.0, "Width": 264.0}], "MaxHeight": 53.0, "MinTop": 1623.0}, {"LineText": "ADDRESS :BLK. 20 LOT 55 DECA HOMES", "Words": [{"WordText": "ADDRESS", "Left": 13.0, "Top": 1675.0, "Height": 50.0, "Width": 169.0}, {"WordText": ":", "Left": 188.0, "Top": 1675.0, "Height": 50.0, "Width": 94.0}, {"WordText": "BLK", "Left": 188.0, "Top": 1675.0, "Height": 50.0, "Width": 94.0}, {"WordText": ".", "Left": 188.0, "Top": 1675.0, "Height": 50.0, "Width": 94.0}, {"WordText": "20", "Left": 288.0, "Top": 1675.0, "Height": 50.0, "Width": 56.0}, {"WordText": "LOT", "Left": 351.0, "Top": 1675.0, "Height": 50.0, "Width": 75.0}, {"WordText": "55", "Left": 432.0, "Top": 1675.0, "Height": 50.0, "Width": 56.0}, {"WordText": "DECA", "Left": 494.0, "Top": 1675.0, "Height": 50.0, "Width": 100.0}, {"WordText": "HOMES", "Left": 600.0, "Top": 1675.0, "Height": 50.0, "Width": 115.0}], "MaxHeight": 50.0, "MinTop": 1675.0}, {"LineText": "PANDAC PAVIA ILOILO", "Words": [{"WordText": "PANDAC", "Left": 200.0, "Top": 1728.0, "Height": 46.0, "Width": 138.0}, {"WordText": "PAVIA", "Left": 344.0, "Top": 1728.0, "Height": 46.0, "Width": 126.0}, {"WordText": "ILOILO", "Left": 476.0, "Top": 1728.0, "Height": 46.0, "Width": 134.0}], "MaxHeight": 46.0, "MinTop": 1728.0}, {"LineText": "TIN M", "Words": [{"WordText": "TIN", "Left": 13.0, "Top": 1780.0, "Height": 43.0, "Width": 70.0}, {"WordText": "M", "Left": 88.0, "Top": 1780.0, "Height": 43.0, "Width": 40.0}], "MaxHeight": 43.0, "MinTop": 1780.0}, {"LineText": ":944185225-000", "Words": [{"WordText": ":", "Left": 184.0, "Top": 1780.0, "Height": 46.0, "Width": 302.0}, {"WordText": "944185225", "Left": 184.0, "Top": 1780.0, "Height": 46.0, "Width": 302.0}, {"WordText": "-", "Left": 184.0, "Top": 1780.0, "Height": 46.0, "Width": 302.0}, {"WordText": "000", "Left": 184.0, "Top": 1780.0, "Height": 46.0, "Width": 302.0}], "MaxHeight": 46.0, "MinTop": 1780.0}, {"LineText": "Accred. #: 00000000000", "Words": [{"WordText": "Accred", "Left": 13.0, "Top": 1833.0, "Height": 46.0, "Width": 144.0}, {"WordText": ".", "Left": 13.0, "Top": 1833.0, "Height": 46.0, "Width": 144.0}, {"WordText": "#:", "Left": 163.0, "Top": 1833.0, "Height": 46.0, "Width": 40.0}, {"WordText": "00000000000", "Left": 209.0, "Top": 1833.0, "Height": 46.0, "Width": 234.0}], "MaxHeight": 46.0, "MinTop": 1833.0}, {"LineText": "05/08/2015-07/31/2025", "Words": [{"WordText": "05", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "/", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "08", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "/", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "2015", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "-", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "07", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "/", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "31", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "/", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}, {"WordText": "2025", "Left": 13.0, "Top": 1886.0, "Height": 46.0, "Width": 449.0}], "MaxHeight": 46.0, "MinTop": 1886.0}, {"LineText": "Pernit #:FP0-0000000-00000", "Words": [{"WordText": "Pernit", "Left": 10.0, "Top": 1938.0, "Height": 49.0, "Width": 141.0}, {"WordText": "#:", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}, {"WordText": "FP0", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}, {"WordText": "-", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}, {"WordText": "0000000", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}, {"WordText": "-", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}, {"WordText": "00000", "Left": 157.0, "Top": 1938.0, "Height": 49.0, "Width": 410.0}], "MaxHeight": 49.0, "MinTop": 1938.0}, {"LineText": "THANK YOU", "Words": [{"WordText": "THANK", "Left": 423.0, "Top": 1991.0, "Height": 43.0, "Width": 121.0}, {"WordText": "YOU", "Left": 549.0, "Top": 1991.0, "Height": 43.0, "Width": 71.0}], "MaxHeight": 43.0, "MinTop": 1991.0}, {"LineText": "PLEASE COME AGAIM", "Words": [{"WordText": "PLEASE", "Left": 308.0, "Top": 2043.0, "Height": 43.0, "Width": 172.0}, {"WordText": "COME", "Left": 485.0, "Top": 2043.0, "Height": 43.0, "Width": 97.0}, {"WordText": "AGAIM", "Left": 587.0, "Top": 2043.0, "Height": 43.0, "Width": 118.0}], "MaxHeight": 43.0, "MinTop": 2043.0}, {"LineText": "THIS SERVE AS AN OFFICIAL RECEIPE", "Words": [{"WordText": "THIS", "Left": 171.0, "Top": 2092.0, "Height": 50.0, "Width": 94.0}, {"WordText": "SERVE", "Left": 271.0, "Top": 2092.0, "Height": 50.0, "Width": 119.0}, {"WordText": "AS", "Left": 396.0, "Top": 2092.0, "Height": 50.0, "Width": 56.0}, {"WordText": "AN", "Left": 459.0, "Top": 2092.0, "Height": 50.0, "Width": 56.0}, {"WordText": "OFFICIAL", "Left": 521.0, "Top": 2092.0, "Height": 50.0, "Width": 188.0}, {"WordText": "RECEIPE", "Left": 715.0, "Top": 2092.0, "Height": 50.0, "Width": 158.0}], "MaxHeight": 50.0, "MinTop": 2092.0}], "HasOverlay": true}, "TextOrientation": "0", "FileParseExitCode": 1, "ParsedText": "BVSU Multi Purpose Cooperative\nLuna Street Lapaz\nIloslo City\nBy: WVSU MPC\nVAT TIN NO. :000-000-000-000\nSerial. No. WIES7WS\nMach ID: 000000000000000000\n000036410\n10-25-2023\nTime\ngampay\nInvoice d\nDate\nCashier\nSold TO:\nBus. Name:\nTIN:\nAddress:\nQTV\nDESC\nCOXE 195ML\nNet Of VAT\nTotal Que\nCash Payment\nSold To:\nBus. Name:\nTIN:\nAddress:\n01:29:49 PM\nTotal\n13.00\n18.61\n13.00\n20.00\nVAT Amt\nTotal Que\nChange\n7.00\nTr 8: 000036513\nSUPPLIER : AVAMICA COMPUTER TECHNOLOGIES\nADDRESS :BLK. 20 LOT 55 DECA HOMES\nPANDAC PAVIA ILOILO\nTIN M\n:944185225-000\nAccred. #: 00000000000\n05/08/2015-07/31/2025\nPernit #:FP0-0000000-00000\nTHANK YOU\nPLEASE COME AGAIM\nTHIS SERVE AS AN OFFICIAL RECEIPE", "ErrorMessage": "", "ErrorDetails": ""}], "OCRExitCode": 1, "IsErroredOnProcessing": false, "ProcessingTimeInMilliseconds": "656", "SearchablePDFURL": "Searchable PDF not generated as it was not requested."}
|
|
|
|
output_folders/20240517_115717/sample_coop_preprocessed.jpg
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Binary file (555 kB)
|
|
output_folders/20240517_115717/uploads/receipt_19.jpg
DELETED
Binary file (611 kB)
|
|
output_folders/20240517_115717/uploads/sample_711.jpg
DELETED
Binary file (682 kB)
|
|
output_folders/20240517_115717/uploads/sample_coop.jpg
DELETED
Binary file (592 kB)
|
|
packages.txt
DELETED
@@ -1 +0,0 @@
|
|
1 |
-
python3-opencv
|
|
|
|
requirements+old.txt
DELETED
@@ -1,255 +0,0 @@
|
|
1 |
-
|
2 |
-
|
3 |
-
|
4 |
-
absl-py==2.0.0
|
5 |
-
aiofiles==23.2.1
|
6 |
-
aiohttp==3.8.5
|
7 |
-
aiosignal==1.3.1
|
8 |
-
altair==5.1.1
|
9 |
-
annotated-types==0.6.0
|
10 |
-
anyio==3.7.1
|
11 |
-
argon2-cffi==23.1.0
|
12 |
-
argon2-cffi-bindings==21.2.0
|
13 |
-
asttokens==2.2.1
|
14 |
-
astunparse==1.6.3
|
15 |
-
async-timeout==4.0.3
|
16 |
-
attrs==23.1.0
|
17 |
-
Babel==2.12.1
|
18 |
-
backcall==0.2.0
|
19 |
-
# backports.functools-lru-cache @ file:///home/conda/feedstock_root/build_artifacts/backports.functools_lru_cache_1687772187254/work
|
20 |
-
beautifulsoup4==4.12.2
|
21 |
-
bleach==6.0.0
|
22 |
-
blinker==1.6.2
|
23 |
-
blis==0.7.11
|
24 |
-
Bottleneck==1.3.7
|
25 |
-
bs4==0.0.1
|
26 |
-
# cached-property @ file:///home/conda/feedstock_root/build_artifacts/cached_property_1615209429212/work
|
27 |
-
cachetools==5.3.1
|
28 |
-
catalogue==2.0.10
|
29 |
-
certifi==2023.7.22
|
30 |
-
cffi==1.15.1
|
31 |
-
charset-normalizer==3.2.0
|
32 |
-
click==8.1.7
|
33 |
-
cloudpathlib==0.16.0
|
34 |
-
colabcode==0.3.0
|
35 |
-
colabconnect @ git+https://github.com/amitness/colab-connect.git@a196621de80d6eb1b73b5c8261cc223c96bae479
|
36 |
-
colorama==0.4.6
|
37 |
-
comm==0.1.3
|
38 |
-
confection==0.1.4
|
39 |
-
contourpy==1.1.0
|
40 |
-
cycler==0.11.0
|
41 |
-
cymem==2.0.8
|
42 |
-
datasets @ git+https://github.com/huggingface/datasets.git@a1e1867e932f14233244fb25713f3c94c46ff50a
|
43 |
-
debugpy==1.6.7
|
44 |
-
decorator==5.1.1
|
45 |
-
defusedxml==0.7.1
|
46 |
-
dill==0.3.4
|
47 |
-
editdistance==0.6.2
|
48 |
-
efficientnet==1.0.0
|
49 |
-
essential-generators==1.0
|
50 |
-
et-xmlfile==1.1.0
|
51 |
-
exceptiongroup==1.1.3
|
52 |
-
executing==1.2.0
|
53 |
-
fastai==1.0.61
|
54 |
-
fastapi==0.109.2
|
55 |
-
fastcore==1.5.29
|
56 |
-
fastdownload==0.0.7
|
57 |
-
fastjsonschema==2.18.0
|
58 |
-
fastprogress==1.0.3
|
59 |
-
ffmpy==0.3.2
|
60 |
-
filelock==3.12.2
|
61 |
-
Flask==2.3.3
|
62 |
-
Flask-Cors==4.0.0
|
63 |
-
flatbuffers==23.5.26
|
64 |
-
fonttools==4.42.1
|
65 |
-
frozenlist==1.4.0
|
66 |
-
fsspec==2023.6.0
|
67 |
-
gast==0.4.0
|
68 |
-
gitdb==4.0.10
|
69 |
-
GitPython==3.1.37
|
70 |
-
google-auth==2.23.0
|
71 |
-
google-auth-oauthlib==1.0.0
|
72 |
-
google-pasta==0.2.0
|
73 |
-
gradio==4.18.0
|
74 |
-
gradio_client==0.10.0
|
75 |
-
grpcio==1.58.0
|
76 |
-
h11==0.14.0
|
77 |
-
# h5py==3.9.0
|
78 |
-
httpcore==1.0.2
|
79 |
-
httpx==0.26.0
|
80 |
-
huggingface-hub==0.20.3
|
81 |
-
idna==3.4
|
82 |
-
imageio==2.31.3
|
83 |
-
imgaug==0.4.0
|
84 |
-
# importlib-metadata @ file:///home/conda/feedstock_root/build_artifacts/importlib-metadata_1688754491823/work
|
85 |
-
importlib-resources==6.1.1
|
86 |
-
imutils==0.5.4
|
87 |
-
ipykernel==6.24.0
|
88 |
-
ipython==8.14.0
|
89 |
-
ipython-genutils==0.2.0
|
90 |
-
itsdangerous==2.1.2
|
91 |
-
jedi==0.18.2
|
92 |
-
Jinja2==3.1.2
|
93 |
-
joblib==1.3.2
|
94 |
-
json5==0.9.14
|
95 |
-
jsonify==0.5
|
96 |
-
jsonschema==4.19.1
|
97 |
-
jsonschema-specifications==2023.7.1
|
98 |
-
jupyter-server==1.24.0
|
99 |
-
jupyter_client==8.3.0
|
100 |
-
jupyter_core==5.3.1
|
101 |
-
jupyterlab==3.0.7
|
102 |
-
jupyterlab-pygments==0.2.2
|
103 |
-
jupyterlab_server==2.25.0
|
104 |
-
keras==2.15.0
|
105 |
-
Keras-Applications==1.0.8
|
106 |
-
keras-ocr==0.9.3
|
107 |
-
kiwisolver==1.4.5
|
108 |
-
langcodes==3.3.0
|
109 |
-
lazy_loader==0.3
|
110 |
-
libclang==16.0.6
|
111 |
-
Markdown==3.4.4
|
112 |
-
markdown-it-py==3.0.0
|
113 |
-
MarkupSafe==2.1.3
|
114 |
-
matplotlib==3.7.2
|
115 |
-
matplotlib-inline==0.1.6
|
116 |
-
mdurl==0.1.2
|
117 |
-
mistune==3.0.1
|
118 |
-
ml-dtypes==0.2.0
|
119 |
-
mpmath==1.3.0
|
120 |
-
# mtcnn @ file:///home/conda/feedstock_root/build_artifacts/mtcnn_1629221401070/work
|
121 |
-
multidict==6.0.4
|
122 |
-
multiprocess==0.70.12.2
|
123 |
-
murmurhash==1.0.10
|
124 |
-
nbclassic==0.3.7
|
125 |
-
nbclient==0.8.0
|
126 |
-
nbconvert==7.8.0
|
127 |
-
nbformat==5.9.2
|
128 |
-
nest-asyncio==1.4.3
|
129 |
-
networkx==3.1
|
130 |
-
notebook==6.4.5
|
131 |
-
notebook_shim==0.2.3
|
132 |
-
npm==0.1.1
|
133 |
-
numexpr==2.8.8
|
134 |
-
numpy==1.24.3
|
135 |
-
nvidia-ml-py3==7.352.0
|
136 |
-
oauthlib==3.2.2
|
137 |
-
opencv-python==4.8.1.78
|
138 |
-
openpyxl==3.1.2
|
139 |
-
opt-einsum==3.3.0
|
140 |
-
optional-django==0.1.0
|
141 |
-
orjson==3.9.13
|
142 |
-
outcome==1.2.0
|
143 |
-
packaging==23.1
|
144 |
-
pandas==2.0.3
|
145 |
-
pandocfilters==1.5.0
|
146 |
-
parso==0.8.3
|
147 |
-
pickleshare==0.7.5
|
148 |
-
Pillow==9.5.0
|
149 |
-
# platformdirs @ file:///home/conda/feedstock_root/build_artifacts/platformdirs_1690813113769/work
|
150 |
-
preshed==3.0.9
|
151 |
-
prometheus-client==0.17.1
|
152 |
-
prompt-toolkit==3.0.39
|
153 |
-
protobuf==4.23.4
|
154 |
-
psutil==5.9.5
|
155 |
-
pure-eval==0.2.2
|
156 |
-
pyarrow==13.0.0
|
157 |
-
pyasn1==0.5.0
|
158 |
-
pyasn1-modules==0.3.0
|
159 |
-
pyclipper==1.3.0.post5
|
160 |
-
pycparser==2.21
|
161 |
-
pydantic==2.5.2
|
162 |
-
pydantic_core==2.14.5
|
163 |
-
pydeck==0.8.1b0
|
164 |
-
pydicom==2.4.3
|
165 |
-
pydub==0.25.1
|
166 |
-
Pygments==2.15.1
|
167 |
-
pyngrok==7.0.0
|
168 |
-
pyparsing==3.0.9
|
169 |
-
PySocks==1.7.1
|
170 |
-
pytesseract==0.3.10
|
171 |
-
python-dateutil==2.8.2
|
172 |
-
python-multipart==0.0.9
|
173 |
-
pytz==2023.3
|
174 |
-
# pywin32==306
|
175 |
-
pywinpty==2.0.11
|
176 |
-
# PyYAML @ file:///D:/bld/pyyaml_1695373635661/work
|
177 |
-
pyzmq==25.1.0
|
178 |
-
referencing==0.30.2
|
179 |
-
regex==2023.8.8
|
180 |
-
requests==2.31.0
|
181 |
-
requests-oauthlib==1.3.1
|
182 |
-
rich==13.5.3
|
183 |
-
rpds-py==0.10.3
|
184 |
-
rsa==4.9
|
185 |
-
ruff==0.2.1
|
186 |
-
safetensors==0.3.2
|
187 |
-
scikit-image==0.22.0
|
188 |
-
scikit-learn==1.3.2
|
189 |
-
scipy==1.11.2
|
190 |
-
seaborn==0.12.2
|
191 |
-
selenium==4.12.0
|
192 |
-
semantic-version==2.10.0
|
193 |
-
Send2Trash==1.8.2
|
194 |
-
seqeval==1.2.2
|
195 |
-
shapely==2.0.2
|
196 |
-
shellingham==1.5.4
|
197 |
-
six==1.16.0
|
198 |
-
smart-open==6.4.0
|
199 |
-
smmap==5.0.1
|
200 |
-
sniffio==1.3.0
|
201 |
-
sortedcontainers==2.4.0
|
202 |
-
soupsieve==2.5
|
203 |
-
spacy==3.7.2
|
204 |
-
spacy-legacy==3.0.12
|
205 |
-
spacy-loggers==1.0.5
|
206 |
-
srsly==2.4.8
|
207 |
-
stack-data==0.6.2
|
208 |
-
starlette==0.36.3
|
209 |
-
streamlit==1.27.0
|
210 |
-
sympy==1.12
|
211 |
-
tenacity==8.2.3
|
212 |
-
tensorboard==2.15.1
|
213 |
-
tensorboard-data-server==0.7.1
|
214 |
-
tensorflow==2.15.0
|
215 |
-
tensorflow-estimator==2.15.0
|
216 |
-
tensorflow-intel==2.15.0
|
217 |
-
tensorflow-io-gcs-filesystem==0.31.0
|
218 |
-
termcolor==2.3.0
|
219 |
-
terminado==0.17.1
|
220 |
-
thinc==8.2.2
|
221 |
-
threadpoolctl==3.2.0
|
222 |
-
tifffile==2023.12.9
|
223 |
-
tinycss2==1.2.1
|
224 |
-
tokenizers==0.13.3
|
225 |
-
toml==0.10.2
|
226 |
-
tomlkit==0.12.0
|
227 |
-
toolz==0.12.0
|
228 |
-
torch==2.1.1
|
229 |
-
torchvision==0.16.1
|
230 |
-
tornado==6.3.2
|
231 |
-
tqdm==4.66.1
|
232 |
-
traitlets==5.9.0
|
233 |
-
transformers==4.31.0
|
234 |
-
trio==0.22.2
|
235 |
-
trio-websocket==0.10.4
|
236 |
-
typer==0.9.0
|
237 |
-
typing_extensions==4.9.0
|
238 |
-
tzdata==2023.3
|
239 |
-
tzlocal==5.0.1
|
240 |
-
urllib3==1.26.16
|
241 |
-
uvicorn==0.27.1
|
242 |
-
validators==0.22.0
|
243 |
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wasabi==1.1.2
|
244 |
-
watchdog==3.0.0
|
245 |
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wcwidth==0.2.6
|
246 |
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weasel==0.3.4
|
247 |
-
webencodings==0.5.1
|
248 |
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websocket-client==1.6.3
|
249 |
-
websockets==11.0.3
|
250 |
-
Werkzeug==2.3.7
|
251 |
-
wrapt==1.14.1
|
252 |
-
wsproto==1.2.0
|
253 |
-
xxhash==3.3.0
|
254 |
-
yarl==1.9.2
|
255 |
-
# zipp @ file:///home/conda/feedstock_root/build_artifacts/zipp_1689374466814/work
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