venom11/cardetection13232

1import gradio as gr
2import easyocr
3import cv2
4import numpy as np
5from PIL import Image
6
7# Create an EasyOCR Reader
8reader = easyocr.Reader(['en'])
9
10def process_image(image):
11    # Convert the PIL image to a numpy array (compatible with OpenCV)
12    image_np = np.array(image)
13
14    # Convert the image to RGB (OpenCV loads as BGR, EasyOCR expects RGB)
15    image_rgb = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
16
17    # Use EasyOCR to read text from the image
18    result = reader.readtext(image_rgb)
19
20    # Draw bounding boxes around detected text
21    for (bbox, text, prob) in result:
22        (top_left, top_right, bottom_right, bottom_left) = bbox
23        top_left = tuple(map(int, top_left))
24        bottom_right = tuple(map(int, bottom_right))
25        cv2.rectangle(image_np, top_left, bottom_right, (0, 255, 0), 2)
26    
27    # Convert back to RGB for display
28    result_image = Image.fromarray(cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB))
29    
30    # Combine detected text and their confidence scores
31    detected_text = "\n".join([f"Detected text: {text}, Confidence: {prob:.2f}" for (_, text, prob) in result])
32    
33    return result_image, detected_text
34
35# Gradio Interface
36interface = gr.Interface(
37    fn=process_image, 
38    inputs="image", 
39    outputs=["image", "text"], 
40    title="OCR with EasyOCR", 
41    description="Upload an image, and the system wi ll detect text using EasyOCR and display it."
42)
43
44# Launch the interface
45interface.launch()
46