Create app.py

app.py

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+import gradio as gr
+import cv2
+import easyocr
+import numpy as np
+
+# Initialize the EasyOCR reader
+reader = easyocr.Reader(['en'], gpu=False)
+
+# Function to perform text detection and return the image with bounding boxes
+def detect_text(image):
+    # Convert the image to OpenCV format
+    image_cv = cv2.imdecode(np.frombuffer(image.read(), np.uint8), cv2.IMREAD_COLOR)
+
+    # Detect text on the image
+    text_results = reader.readtext(image_cv)
+
+    # Draw bounding boxes and text on the image
+    for result in text_results:
+        bbox, text, score = result
+        if score > 0.25:
+            cv2.rectangle(image_cv, bbox[0], bbox[2], (0, 255, 0), 5)
+            cv2.putText(image_cv, text, bbox[0], cv2.FONT_HERSHEY_COMPLEX, 0.65, (255, 0, 0), 2)
+
+    # Convert the processed image back to a format that Gradio can display
+    image_with_boxes = cv2.imencode('.jpg', image_cv)[1].tobytes()
+    
+    return image_with_boxes
+
+# Create a Gradio interface
+iface = gr.Interface(
+    fn=detect_text,
+    inputs=gr.inputs.Image(type="file", label="Upload an image"),
+    outputs=gr.outputs.Image(type="pil"),
+    title="EasyOCR Text Detection",
+    description="Upload an image and detect text with EasyOCR",
+    live=True,
+)
+
+# Launch the Gradio app
+iface.launch()