Update app.py

app.py

@@ -1,58 +1,30 @@
-from flask import Flask, request, render_template
 import cv2
 import numpy as np
 from PIL import Image
 import io
-from mtcnn import MTCNN  # Import the MTCNN class from your mtcnn.py file
+from mtcnn import MTCNN
+import gradio as gr
 
-app = Flask(__name__)
 detector = MTCNN()
 
-def detect_faces_and_draw(image_bytes):
-    """Detects faces in the image bytes and draws bounding boxes and keypoints."""
-    nparr = np.frombuffer(image_bytes, np.uint8)
-    img = cv2.imdecode(nparr, cv2.IMREAD_COLOR)
-    img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+def detect_faces_gradio(image):
+    img_rgb = cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR)
     faces = detector.detect_faces(img_rgb)
-
+    processed_img = np.array(image).copy()
     if faces:
         for face in faces:
             bounding_box = face['box']
             keypoints = face['keypoints']
-
-            cv2.rectangle(img,
+            cv2.rectangle(processed_img,
                           (bounding_box[0], bounding_box[1]),
                           (bounding_box[0] + bounding_box[2], bounding_box[1] + bounding_box[3]),
                           (0, 255, 0),
                           2)
-
             for key, value in keypoints.items():
-                cv2.circle(img, (int(value[0]), int(value[1])), 2, (0, 0, 255), 2)
-
-        # Convert the processed image back to bytes for display
-        img_pil = Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGR2RGB))
-        img_buffer = io.BytesIO()
-        img_pil.save(img_buffer, format="JPEG")
-        return img_buffer.getvalue()
-    else:
-        return None
-
-@app.route('/', methods=['GET', 'POST'])
-def upload_file():
-    if request.method == 'POST':
-        if 'file' not in request.files:
-            return render_template('index.html', error='No file part')
-        file = request.files['file']
-        if file.filename == '':
-            return render_template('index.html', error='No selected file')
-        if file:
-            image_bytes = file.read()
-            processed_image_bytes = detect_faces_and_draw(image_bytes)
-            if processed_image_bytes:
-                return render_template('index.html', result=True, image_data=f"data:image/jpeg;base64,{processed_image_bytes.hex()}")
-            else:
-                return render_template('index.html', error='No faces detected')
-    return render_template('index.html')
+                cv2.circle(processed_img, (int(value[0]), int(value[1])), 2, (0, 0, 255), 2)
+    return processed_img
 
-if __name__ == '__main__':
-    app.run(debug=True)
+iface = gr.Interface(fn=detect_faces_gradio, inputs=gr.Image(type="pil"), outputs="image",
+                     title="MTCNN Face Detection",
+                     description="Upload an image and see the detected faces and landmarks.")
+iface.launch()