Update app.py

app.py

@@ -6,38 +6,25 @@ import kornia as K
 from kornia.core import Tensor
 from kornia.contrib import FaceDetector, FaceDetectorResult, FaceKeypoint
 
-
-
-
 def draw_keypoint(img: np.ndarray, det: FaceDetectorResult, kpt_type: FaceKeypoint) -> np.ndarray:
     kpt = det.get_keypoint(kpt_type).int().tolist()
     return cv2.circle(img, kpt, 2, (255, 0, 0), 2)
 
-
-
 def detect(img_raw):
-
     # preprocess
     if img_raw is not None and len(img_raw.shape) == 3:
-        img = K.image_to_tensor(img_raw, keepdim=False)
+        img = K.utils.image_to_tensor(img_raw, keepdim=False)
         img = K.color.bgr_to_rgb(img.float())
-
-
         # create the detector and find the faces !
         face_detection = FaceDetector()
-
         with torch.no_grad():
             dets = face_detection(img)
         dets = [FaceDetectorResult(o) for o in dets[0]]
-
         img_vis = img_raw.copy()
-
         vis_threshold = 0.8
-
         for b in dets:
             if b.score < vis_threshold:
                 continue
-
             # Draw face bounding box
             img_vis = cv2.rectangle(img_vis, b.top_left.int().tolist(), b.bottom_right.int().tolist(), (0, 255, 0), 4)
             # Draw Keypoints
@@ -46,30 +33,26 @@ def detect(img_raw):
             img_vis = draw_keypoint(img_vis, b, FaceKeypoint.NOSE)
             img_vis = draw_keypoint(img_vis, b, FaceKeypoint.MOUTH_LEFT)
             img_vis = draw_keypoint(img_vis, b, FaceKeypoint.MOUTH_RIGHT)
-
         return img_vis
 
-
-
 title = "Kornia Face Detection"
 description = "<p style='text-align: center'>This is a Gradio demo for Kornia's Face Detection.</p><p style='text-align: center'>To use it, simply upload your image, or click one of the examples to load them</p>"
 article = "<p style='text-align: center'><a href='https://kornia.readthedocs.io/en/latest/' target='_blank'>Kornia Docs</a> | <a href='https://github.com/kornia/kornia' target='_blank'>Kornia Github Repo</a> | <a href='https://kornia.readthedocs.io/en/latest/applications/face_detection.html' target='_blank'>Kornia Face Detection Tutorial</a></p>"
-
 examples = ['sample.jpg']
 
-
-face = gr.Interface(
-    detect,
-    gr.inputs.Image(type="numpy"),
-    gr.Image(type="pil", interactive=False),
-    examples=examples,
-    title=title,
-    description=description,
-    article=article,
-    live=True,
-    allow_flagging="never"
-)
-
-
-face.launch()
-
+with gr.Blocks(title=title) as demo:
+    gr.Markdown(f"# {title}")
+    gr.Markdown(description)
+    
+    with gr.Row():
+        input_image = gr.Image(type="numpy", label="Input Image")
+        output_image = gr.Image(type="numpy", label="Detected Faces")
+    
+    gr.Examples(examples, inputs=input_image)
+    
+    input_image.change(fn=detect, inputs=input_image, outputs=output_image)
+    
+    gr.Markdown(article)
+
+if __name__ == "__main__":
+    demo.launch()