Update app.py

app.py

@@ -3,15 +3,14 @@ import mediapipe as mp
 import numpy as np
 import cv2
 
-title = "Hugging Face Me"
-description = " Demo for overlaying the Hugging Face logo on your face using the Mediapipe Face Detection model."
+title = "Mishigify Me"
+description = " Demo for adding some mishig to this"
 article = "<p style='text-align: center'><a href='https://google.github.io/mediapipe/solutions/face_detection.html' target='_blank'>Mediapipe Face Detection</a> | <a href='https://github.com/google/mediapipe' target='_blank'>Github Repo</a></p>"
 
 mp_face_detection = mp.solutions.face_detection
 mp_drawing = mp.solutions.drawing_utils
 
-def draw_huggingfaces(image, results):
-    
+def draw_mishigs(image, results):
     height, width, _ = image.shape
 
     output_img = image.copy()
@@ -29,8 +28,7 @@ def draw_huggingfaces(image, results):
     return output_img
 
 
-def huggingface_me(image):
-
+def mishig_me(image):
     with mp_face_detection.FaceDetection(
         model_selection=0, 
         min_detection_confidence=0.5) as face_detection:
@@ -45,14 +43,11 @@ huggingface_image = cv2.imread("images/hugging-face.png",  cv2.IMREAD_UNCHANGED)
 huggingface_image = cv2.cvtColor(huggingface_image, cv2.COLOR_BGRA2RGBA)
 huggingface_landmarks = np.array([[747,697],[1289,697],[1022,1116]], dtype=np.float32)
 
-webcam_image = gr.inputs.Image(label="Input Image", source="webcam")
-output_image = gr.outputs.Image(label="Output Image")
 
-gr.Interface(huggingface_me, 
-            live=True, 
-            inputs=webcam_image, 
-            outputs=output_image,
+gr.Interface(mishig_me, 
+            inputs=gr.Image(label="Input Image", source="webcam"), 
+            outputs=gr.Image(label="Output Image"),
             title=title,
             description=description,
-            article=article, ).launch()
+            article=article).launch()