Update app.py

app.py

@@ -72,122 +72,29 @@ def face_compare(frame1, frame2):
     return detections_table + matches_table
 
 def check_liveness(frame):
-    url = "https://faceapi.miniai.live/face_liveness_check"
-    file = {'file': open(frame, 'rb')}
-
-    r = requests.post(url=url, files=file)
-
-    faceCount = None
-
-    response_data = r.json()
-
-    for item in response_data.get('face_state', []):
-        if 'faceCount' in item:
-            faceCount = item['faceCount']
-            break
-
-    faces = None
-    live_result = []
-    live_result.append(f"<table><tr><th>FaceID</th><th>Age</th><th>Gender</th><th>Liveness</th></tr>")
-
-    for item in response_data.get('face_state', []):
-        if item.get('FaceID'):
-            faceID = item.get('FaceID')
-            result = item.get('LivenessCheck')
-            age = item.get('Age')
-            gender = item.get('Gender')
-            live_result.append(f"<tr><td>{faceID}</td><td>{age}</td><td>{gender}</td><td>{result}</td></tr>")
-    live_result.append(f"</table>")
-    live_result = ''.join(live_result)
-
-    try:
-        image = Image.open(frame)        
-
-        for face in r.json().get('faces'):
-            x1 = face.get('x1')
-            y1 = face.get('y1')
-            x2 = face.get('x2')
-            y2 = face.get('y2')
-
-            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
-
-            face_image = face_image.resize((int(resized_w), int(resized_h)))
-
-            if faces is None:
-                faces = face_image
-            else:
-                new_image = Image.new('RGB',(faces.width + face_image.width + 10, 150), (80,80,80))
-
-                new_image.paste(faces,(0,0))
-                new_image.paste(face_image,(faces.width + 10, 0))
-                faces = new_image.copy()
-    except:
-        pass
-
-    return [faces, live_result]
-
-def face_emotion(frame):
-    url = "https://faceapi.miniai.live/face_emotion"
-    file = {'file': open(frame, 'rb')}
-
-    r = requests.post(url=url, files=file)
-
-    emotion_result = []
-    emotion_result.append(f"<table><tr><td>Emotional Result : </td><td>{r.json().get('emotion_result')}</td></tr>")
-    emotion_result.append(f"</table>")
-    emotion_result = ''.join(emotion_result)
-
-    faces = None
-
-    try:
-        image = Image.open(frame)        
-
-        for face in r.json().get('faces'):
-            x1 = face.get('x1')
-            y1 = face.get('y1')
-            x2 = face.get('x2')
-            y2 = face.get('y2')
-
-            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
-
-            face_image = face_image.resize((int(resized_w), int(resized_h)))
-
-            if faces is None:
-                faces = face_image
-            else:
-                new_image = Image.new('RGB',(faces.width + face_image.width + 10, 150), (80,80,80))
-
-                new_image.paste(faces,(0,0))
-                new_image.paste(face_image,(faces.width + 10, 0))
-                faces = new_image.copy()
-    except:
-        pass
+    url = "https://facelive.miniai.live/api/check_livenes"
+    files = {'image': open(frame, 'rb')}
+    r = requests.post(url=url, files=files)
 
-    return [faces, emotion_result]
+    html = None
+    table_value = ""
+
+    for key, value in r.json().items():
+        row_value = ("<tr>"
+                        "<td>{key}</td>"
+                        "<td>{value}</td>"
+                    "</tr>".format(key=key, value=value))
+        table_value = table_value + row_value
+
+    html = ("<table>"
+                "<tr>"
+                    "<th style=""width:30%"">Field</th>"
+                    "<th style=""width:50%"">Value</th>"
+                "</tr>"
+                "{table_value}"
+                "</table>".format(table_value=table_value))
+    
+    return html
 
 # APP Interface
 with gr.Blocks() as MiniAIdemo:
@@ -251,7 +158,7 @@ with gr.Blocks() as MiniAIdemo:
             btn_f_match.click(face_compare, inputs=[im_match_in1, im_match_in2], outputs=txt_compare_out)
         with gr.Tab("Face Liveness Detection"):
             with gr.Row():
-                with gr.Column(scale=1):
+                with gr.Column():
                     im_liveness_in = gr.Image(type='filepath', height=300)
                     gr.Examples(
                         [
@@ -267,36 +174,9 @@ with gr.Blocks() as MiniAIdemo:
                         inputs=im_liveness_in
                     )
                     btn_f_liveness = gr.Button("Check Liveness!", variant='primary')
-                with gr.Blocks():
-                    with gr.Row():
-                        with gr.Column():
-                            im_liveness_out = gr.Image(label="Croped Face", type="pil", scale=1)
-                        with gr.Column():
-                            livness_result_output = gr.HTML()
-            btn_f_liveness.click(check_liveness, inputs=im_liveness_in, outputs=[im_liveness_out, livness_result_output])
-        with gr.Tab("Face Emotional Recognition"):
-            with gr.Row():
                 with gr.Column():
-                    im_emotion_in = gr.Image(type='filepath', height=300)
-                    gr.Examples(
-                        [
-                            "images/emotion/1.jpg",
-                            "images/emotion/2.jpg",
-                            "images/emotion/3.jpg",
-                            "images/emotion/4.jpg",
-                            "images/emotion/5.jpg",
-                            "images/emotion/6.jpg",
-                        ],
-                        inputs=im_emotion_in
-                    )
-                    btn_f_emotion = gr.Button("Check Emotion!", variant='primary')
-                with gr.Blocks():
-                    with gr.Row():
-                        with gr.Column():
-                            im_emotion_out = gr.Image(label="Result Image", type="pil", scale=1)
-                        with gr.Column():
-                            txt_emotion_out = gr.HTML()
-            btn_f_emotion.click(face_emotion, inputs=im_emotion_in, outputs=[im_emotion_out, txt_emotion_out])
+                    livness_result_output = gr.HTML()
+            btn_f_liveness.click(check_liveness, inputs=im_liveness_in, outputs=livness_result_output)
     gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FMiniAiLive%2FFaceRecognition-LivenessDetection-Demo"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FMiniAiLive%2FFaceRecognition-LivenessDetection-Demo&label=VISITORS&labelColor=%2337d67a&countColor=%23ff8a65&style=plastic&labelStyle=none" /></a>')
 if __name__ == "__main__":
     MiniAIdemo.launch()