Update

app.py

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+import gradio as gr
+import requests
+import json
+from PIL import Image
+
+def compare_face(frame1, frame2):
+    url = "https://recognito.p.rapidapi.com/api/face"
+    files = {'image1': open(frame1, 'rb'), 'image2': open(frame2, 'rb')}
+    headers = {"X-RapidAPI-Key": os.environ.get("API_KEY")}
+
+    r = requests.post(url=url, files=files)
+    faces = None
+
+    try:
+        image1 = Image.open(frame1)
+        image2 = Image.open(frame2)
+
+        face1 = None
+        face2 = None
+        image1 = r.json().get('image1')
+        if image1.get('detection') is not None:
+            face = image1.get('face1')
+            x1 = face.get('x')
+            y1 = face.get('y')
+            x2 = x1 + face.get('w')
+            y2 = y1 + face.get('h')
+            if x1 < 0:
+                x1 = 0
+            if y1 < 0:
+                y1 = 0
+            if x2 >= image1.width:
+                x2 = image1.width - 1
+            if y2 >= image1.height:
+                y2 = image1.height - 1
+
+            face1 = image1.crop((x1, y1, x2, y2))
+            face_image_ratio = face1.width / float(face1.height)
+            resized_w = int(face_image_ratio * 150)
+            resized_h = 150
+
+            face1 = face1.resize((int(resized_w), int(resized_h)))
+
+        image2 = r.json().get('image1')
+        if image2.get('face2') is not None:
+            face = image2.get('face2')
+            x1 = face.get('x')
+            y1 = face.get('y')
+            x2 = x1 + face.get('w')
+            y2 = y1 + face.get('h')
+
+            if x1 < 0:
+                x1 = 0
+            if y1 < 0:
+                y1 = 0
+            if x2 >= image2.width:
+                x2 = image2.width - 1
+            if y2 >= image2.height:
+                y2 = image2.height - 1
+
+            face2 = image2.crop((x1, y1, x2, y2))
+            face_image_ratio = face2.width / float(face2.height)
+            resized_w = int(face_image_ratio * 150)
+            resized_h = 150
+
+            face2 = face2.resize((int(resized_w), int(resized_h)))
+        
+        if face1 is not None and face2 is not None:
+            new_image = Image.new('RGB',(face1.width + face2.width + 10, 150), (80,80,80))
+
+            new_image.paste(face1,(0,0))
+            new_image.paste(face2,(face1.width + 10, 0))
+            faces = new_image.copy()
+        elif face1 is not None and face2 is None:
+            new_image = Image.new('RGB',(face1.width + face1.width + 10, 150), (80,80,80))
+
+            new_image.paste(face1,(0,0))
+            faces = new_image.copy()
+        elif face1 is None and face2 is not None:
+            new_image = Image.new('RGB',(face2.width + face2.width + 10, 150), (80,80,80))
+
+            new_image.paste(face2,(face2.width + 10, 0))
+            faces = new_image.copy()
+    except:
+        pass
+
+    return [r.json(), faces]
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # Recognito Face Analysis
+    """
+    )
+    with gr.Row():
+        with gr.Column():
+            compare_face_input1 = gr.Image(type='filepath', height=480)
+            gr.Examples(['gradio/examples/1.jpg', 'gradio/examples/2.jpg'], 
+                        inputs=compare_face_input1)
+            compare_face_button = gr.Button("Compare Face")
+        with gr.Column():
+            compare_face_input2 = gr.Image(type='filepath', height=480)
+            gr.Examples(['gradio/examples/3.jpg', 'gradio/examples/4.jpg'], 
+                        inputs=compare_face_input2)
+        with gr.Column():
+            compare_face_output = gr.Image(type="pil", height=150)
+            compare_result_output = gr.JSON(label='Result')
+
+    compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_result_output, compare_face_output])
+
+demo.launch(server_name="0.0.0.0", server_port=7860)

push.bat

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+git add .
+git commit -m %1
+git push