Update demo.py

demo.py

@@ -4,22 +4,24 @@ import datadog_api_client
 from PIL import Image
 
 def face_crop(image, face_rect):
-    x = face_rect.get('x')
-    y = face_rect.get('y')
-    width = face_rect.get('width')
-    height = face_rect.get('height')
-
-
-    if x < 0:
-        x = 0
-    if y < 0:
-        y = 0
-    if x + width >= image.width:
-        width = image.width - x
-    if y + height >= image.height:
-        height = image.height - y
-
-    face_image = image.crop((x, y, x + width - 1, y + height - 1))
+    x1 = face_rect.get('x1')
+    y1 = face_rect.get('y1')
+    x2 = face_rect.get('x2')
+    y2 = face_rect.get('y2')
+    width = x2 - x1 + 1
+    height = y2 - y2 + 1
+
+
+    if x1 < 0:
+        x1 = 0
+    if y1 < 0:
+        y1 = 0
+    if x2 >= image.width:
+        x2 = image.width - 1
+    if y2 >= image.height:
+        y2 = image.height - 1
+
+    face_image = image.crop((x1, y1, x2, y2))
     face_image_ratio = face_image.width / float(face_image.height)
     resized_w = int(face_image_ratio * 150)
     resized_h = 150
@@ -94,13 +96,12 @@ with gr.Blocks(css=".gradio-container {background-color: #F4E5E0}") as demo:
             with gr.Row():
                 with gr.Column():
                     image_input1 = gr.Image(type='pil')
-                    gr.Examples(['examples/1.webp', 'examples/2.webp', 'examples/3.webp', 'examples/4.webp'], 
+                    gr.Examples(['face_examples/1.jpg', 'face_examples/3.jpg', 'face_examples/7.jpg', 'face_examples/9.jpg'], 
                                 inputs=image_input1)
                 with gr.Column():
                     image_input2 = gr.Image(type='pil')
-                    gr.Examples(['examples/5.webp', 'examples/6.webp', 'examples/7.webp', 'examples/8.webp'], 
+                    gr.Examples(['face_examples/2.jpg', 'face_examples/4.jpg', 'face_examples/8.jpg', 'face_examples/10.jpg'], 
                                 inputs=image_input2)
-            verifyThreshold = gr.Slider(minimum=0, maximum=1, value=0.67, label="Verify Threshold")    
             face_recog_button = gr.Button("Face Recognition")
         with gr.Column(scale=3):
             recog_html_output = gr.HTML()