Create app.py

app.py

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+import gradio as gr
+import face_recognition
+
+
+def run_verification(verification_image, input_image):
+    temp = face_recognition.face_encodings(verification_image)
+    if len(temp) == 1:
+        verification_encoding = face_recognition.face_encodings(verification_image)[0]
+    elif len(temp)>1:
+        return 'Multiple faces detected in verification image ❌. Verification Image must have a single face'
+    else:
+        return 'No face detected in verification image ❌. Verification Image must have a single face'
+    
+    temp = face_recognition.face_encodings(input_image)
+    if len(temp) == 1:
+        input_encoding = face_recognition.face_encodings(input_image)[0]
+        multiple_people=False
+    elif len(temp)>1:
+        input_encoding = face_recognition.face_encodings(input_image)[0]
+        multiple_people=True
+    else:
+        return 'No face detected in Input Image.'
+
+    results = face_recognition.compare_faces([verification_encoding], input_encoding)
+    
+    if results[0]==True and not multiple_people:
+        return 'Facial Verification Successful ✅. Both pictures contain the same person'
+    elif results[0]==True and multiple_people:
+        return 'Facial Verification Successful ✅. Both pictures contain the same person. Input Image contains multiple faces.'
+    else:
+        return 'Facial Verification Failed ❌. Both pictures contain different persons'
+
+with gr.Blocks() as demo:
+    gr.Markdown("# FaceMatch: A Zero Shot Facial Recognition App")
+    gr.Markdown("FaceMatch is a cutting-edge facial recognition application that allows users to compare two images to determine if they depict the same person or not. Unlike traditional facial recognition systems that require a database of known faces, FaceMatch utilizes zero-shot facial recognition technology, which means it can recognize individuals without any prior training using just a single anchor image.")
+    gr.Markdown('''
+Steps to Run:
+1. Upload your image as a reference image.
+2. Upload the input image on which you want to run facial recognition.
+3. Click "Run Facial Recognition" to initiate the process.
+4. View the verification result.
+''')
+    gr.Info('Test')
+    with gr.Row():
+        verification_image = gr.Image(label='Reference Image')
+        input_image = gr.Image(label = 'Input Image')
+    verify_button = gr.Button(value="Run Facial Recognition")
+    output_textbox = gr.Textbox(value="", label="Verification Result")
+    verify_button.click(run_verification, inputs=[verification_image, input_image], outputs=[output_textbox])
+    # upload_button.upload(upload_file, upload_button, file_output)
+
+demo.launch()