Delete app (1).py

app (1).py

@@ -1,45 +0,0 @@
-import gradio as gr
-import easyocr
-import cv2
-import numpy as np
-from PIL import Image
-
-# Create an EasyOCR Reader
-reader = easyocr.Reader(['en'])
-
-def process_image(image):
-    # Convert the PIL image to a numpy array (compatible with OpenCV)
-    image_np = np.array(image)
-
-    # Convert the image to RGB (OpenCV loads as BGR, EasyOCR expects RGB)
-    image_rgb = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
-
-    # Use EasyOCR to read text from the image
-    result = reader.readtext(image_rgb)
-
-    # Draw bounding boxes around detected text
-    for (bbox, text, prob) in result:
-        (top_left, top_right, bottom_right, bottom_left) = bbox
-        top_left = tuple(map(int, top_left))
-        bottom_right = tuple(map(int, bottom_right))
-        cv2.rectangle(image_np, top_left, bottom_right, (0, 255, 0), 2)
-    
-    # Convert back to RGB for display
-    result_image = Image.fromarray(cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB))
-    
-    # Combine detected text and their confidence scores
-    detected_text = "\n".join([f"Detected text: {text}, Confidence: {prob:.2f}" for (_, text, prob) in result])
-    
-    return result_image, detected_text
-
-# Gradio Interface
-interface = gr.Interface(
-    fn=process_image, 
-    inputs="image", 
-    outputs=["image", "text"], 
-    title="OCR with EasyOCR", 
-    description="Upload an image, and the system will detect text using EasyOCR and display it."
-)
-
-# Launch the interface
-interface.launch()