Update app.py

app.py

@@ -1,144 +1,120 @@
+import gradio as gr
+import tensorflow as tf
+import keras_ocr
+import requests
+import cv2
 import os
+import csv
 import numpy as np
-import json
-import shutil
-import requests
-import re as r
-from urllib.request import urlopen
+import pandas as pd
+import huggingface_hub
+from huggingface_hub import Repository
 from datetime import datetime
-from datasets import Image
+import scipy.ndimage.interpolation as inter
+import easyocr
+import datasets
+from datasets import load_dataset, Image
 from PIL import Image
-from huggingface_hub import Repository, upload_file
-
-HF_TOKEN = os.environ.get("HF_TOKEN")
-DATASET_NAME = "OCR-img-to-text"
-DATASET_REPO_URL = "https://huggingface.co/datasets/pragnakalp/OCR-img-to-text"
-DATA_FILENAME = "ocr_data.csv"
-DATA_FILE = os.path.join("ocr_data", DATA_FILENAME)
-DATASET_REPO_ID = "pragnakalp/OCR-img-to-text"
-print("is none?", HF_TOKEN is None)
-REPOSITORY_DIR = "data"
-LOCAL_DIR = 'data_local'
-os.makedirs(LOCAL_DIR,exist_ok=True)
-
-try:
-    hf_hub_download(
-        repo_id=DATASET_REPO_ID,
-        filename=DATA_FILENAME,
-        cache_dir=DATA_DIRNAME,
-        force_filename=DATA_FILENAME
-    )
-    
-except:
-    print("file not found")
+from paddleocr import PaddleOCR
+from save_data import flag
+            
+"""
+Paddle OCR
+"""
+def ocr_with_paddle(img):
+    finaltext = ''
+    ocr = PaddleOCR(lang='en', use_angle_cls=True)
+    # img_path = 'exp.jpeg'
+    result = ocr.ocr(img)
     
-try:
-    repo = Repository(local_dir="ocr_data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN)
-    repo.git_pull()
-except Exception as e:
-    print("Error occurred during git pull:", e)
+    for i in range(len(result[0])):
+        text = result[0][i][1][0]
+        finaltext += ' '+ text
+    return finaltext
 
-# repo = Repository(local_dir="ocr_data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN)
-# repo.git_pull()
+"""
+Keras OCR
+"""
+def ocr_with_keras(img):
+    output_text = ''
+    pipeline=keras_ocr.pipeline.Pipeline()
+    images=[keras_ocr.tools.read(img)]
+    predictions=pipeline.recognize(images)
+    first=predictions[0]
+    for text,box in first:
+        output_text += ' '+ text
+    return output_text
 
-def getIP():
-    ip_address = ''
-    try:
-    	d = str(urlopen('http://checkip.dyndns.com/')
-    			.read())
-    
-    	return r.compile(r'Address: (\d+\.\d+\.\d+\.\d+)').search(d).group(1)
-    except Exception as e:
-        print("Error while getting IP address -->",e)
-        return ip_address
+"""
+easy OCR
+"""
+# gray scale image
+def get_grayscale(image):
+    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
 
-def get_location(ip_addr):
-    location = {}
-    try:
-        ip=ip_addr
+# Thresholding or Binarization
+def thresholding(src):
+    return cv2.threshold(src,127,255, cv2.THRESH_TOZERO)[1]
+def ocr_with_easy(img):
+    gray_scale_image=get_grayscale(img)
+    thresholding(gray_scale_image)
+    cv2.imwrite('image.png',gray_scale_image)
+    reader = easyocr.Reader(['th','en'])
+    bounds = reader.readtext('image.png',paragraph="False",detail = 0)
+    bounds = ''.join(bounds)
+    return bounds
+        
+"""
+Generate OCR
+"""
+def generate_ocr(Method,img):
     
-        req_data={
-            "ip":ip,
-            "token":"pkml123"
-        }
-        url = "https://demos.pragnakalp.com/get-ip-location"
+    text_output = ''
+    if (img).any():
+        add_csv = []
+        image_id = 1
+        print("Method___________________",Method)
+        if Method == 'EasyOCR':
+            text_output = ocr_with_easy(img)
+        if Method == 'KerasOCR':
+            text_output = ocr_with_keras(img)
+        if Method == 'PaddleOCR':
+            text_output = ocr_with_paddle(img)
+       
+        try:
+            flag(Method,text_output,img)
+        except Exception as e:
+            print(e)
+        return text_output
+    else:
+        raise gr.Error("Please upload an image!!!!")
     
-        # req_data=json.dumps(req_data)
-        # print("req_data",req_data)
-        headers = {'Content-Type': 'application/json'}
+    # except Exception as e:
+    #     print("Error in ocr generation ==>",e)
+    #     text_output = "Something went wrong"
+    # return text_output
     
-        response = requests.request("POST", url, headers=headers, data=json.dumps(req_data))
-        response = response.json()
-        print("response======>>",response)
-        return response
-    except Exception as e:
-        print("Error while getting location -->",e)
-        return location
 
 """
-Save generated details
+Create user interface for OCR demo
 """
-def dump_json(thing,file):
-    with open(file,'w+',encoding="utf8") as f:
-        json.dump(thing,f)
 
-def flag(Method,text_output,input_image):
-    
-    print("saving data------------------------")
-    # try:
-    adversarial_number = 0
-    adversarial_number = 0 if None else adversarial_number
+# image = gr.Image(shape=(300, 300))
+image = gr.Image()
+method = gr.Radio(["PaddleOCR","EasyOCR", "KerasOCR"],value="PaddleOCR")
+output = gr.Textbox(label="Output")
 
-    ip_address= getIP()
-    print("ip_address  :",ip_address)
-    location = get_location(ip_address)
-    print("location   :",location)
+demo = gr.Interface(
+    generate_ocr,
+    [method,image],
+    output,
+    title="Optical Character Recognition",
+    css=".gradio-container {background-color: lightgray} #radio_div {background-color: #FFD8B4; font-size: 40px;}",
+    article = """<p style='text-align: center;'>Feel free to give us your thoughts on this demo and please contact us at 
+                    <a href="mailto:[email protected]" target="_blank">[email protected]</a> 
+                    <p style='text-align: center;'>Developed by: <a href="https://www.pragnakalp.com" target="_blank">Pragnakalp Techlabs</a></p>"""
     
-    metadata_name = datetime.now().strftime('%Y-%m-%d %H-%M-%S')
-    SAVE_FILE_DIR = os.path.join(LOCAL_DIR,metadata_name)
-    os.makedirs(SAVE_FILE_DIR,exist_ok=True)
-    image_output_filename = os.path.join(SAVE_FILE_DIR,'image.png')
-    print("image_output_filename       :",image_output_filename)
-    print(input_image)
-    try:
-        Image.fromarray(input_image).save(image_output_filename)
-        # input_image.save(image_output_filename)
-    except Exception:
-        raise Exception(f"Had issues saving np array image to file")    
 
-    # Write metadata.json to file
-    json_file_path = os.path.join(SAVE_FILE_DIR,'metadata.jsonl')
-    metadata= {'id':metadata_name,'method':Method,'file_name':'image.png',
-                'generated_text':text_output,'ip':ip_address, 'location':location
-                }
-    
-    dump_json(metadata,json_file_path)  
-        
-    # Simply upload the image file and metadata using the hub's upload_file
-    # Upload the image
-    repo_image_path = os.path.join(REPOSITORY_DIR,os.path.join(metadata_name,'image.png'))
-    
-    _ = upload_file(path_or_fileobj = image_output_filename,
-                path_in_repo =repo_image_path,
-                repo_id=DATASET_REPO_ID,
-                repo_type='dataset',
-                token=HF_TOKEN
-            ) 
-
-    # Upload the metadata
-    repo_json_path = os.path.join(REPOSITORY_DIR,os.path.join(metadata_name,'metadata.jsonl'))
-    _ = upload_file(path_or_fileobj = json_file_path,
-                path_in_repo =repo_json_path,
-                repo_id= DATASET_REPO_ID,
-                repo_type='dataset',
-                token=HF_TOKEN
-            )        
-    adversarial_number+=1
-    repo.git_pull()
-
-    url = 'http://pragnakalpdev35.pythonanywhere.com/HF_space_image_to_text'
-    myobj = {'Method': Method,'text_output':text_output,'img':input_image.tolist(),'ip_address':ip_address, 'loc':location}
-    x = requests.post(url, json = myobj)
-    print("mail status code",x.status_code)
-    
-    return "*****Logs save successfully!!!!"
+)
+# demo.launch(enable_queue = False)
+demo.launch()