Create app.py

app.py

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+import re
+import cv2 
+import numpy as np
+import pytesseract
+from pytesseract import Output
+import gradio as gr
+
+#image preprocessing function
+
+#grayscale image
+def get_grayscale(image):
+    return cv2.cvtColor(image,cv2.COLOR_BGR2GRAY)
+
+# noise removal
+def remove_noise(image):
+    return cv2.medianBlur(image,5)
+
+#thresholding
+def thresholding(image):
+    return cv2.threshold(image, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]
+
+#dilation
+def dilate(image):
+    kernel = np.ones((5,5),np.uint8)
+    return cv2.dilate(image, kernel, iterations = 1)
+    
+#erosion
+def erode(image):
+    kernel = np.ones((5,5),np.uint8)
+    return cv2.erode(image, kernel, iterations = 1)
+
+#opening - erosion followed by dilation
+def opening(image):
+    kernel = np.ones((5,5),np.uint8)
+    return cv2.morphologyEx(image, cv2.MORPH_OPEN, kernel)
+
+#canny edge detection
+def canny(image):
+    return cv2.Canny(image, 100, 200)
+
+#skew correction
+def deskew(image):
+    coords = np.column_stack(np.where(image > 0))
+    angle = cv2.minAreaRect(coords)[-1]
+    if angle < -45:
+        angle = -(90 + angle)
+    else:
+        angle = -angle
+    (h, w) = image.shape[:2]
+    center = (w // 2, h // 2)
+    M = cv2.getRotationMatrix2D(center, angle, 1.0)
+    rotated = cv2.warpAffine(image, M, (w, h), flags=cv2.INTER_CUBIC, borderMode=cv2.BORDER_REPLICATE)
+    return rotated
+
+#template matching
+def match_template(image, template):
+    return cv2.matchTemplate(image, template, cv2.TM_CCOEFF_NORMED) 
+
+
+def extract_text_from_image(img):
+
+    # Convert To PIL Image
+    im_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    gray = get_grayscale(im_rgb)
+    noise_remove = remove_noise(gray)
+    # thresh = thresholding(noise_remove)
+    text = pytesseract.image_to_string(noise_remove)
+    return text
+
+app = gr.Interface(
+    fn=extract_text_from_image,
+    inputs=gr.Image(label="upload image"),
+    outputs= gr.Textbox()
+)
+app.launch()