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| import gradio as gr | |
| import requests | |
| import json | |
| from PIL import Image | |
| def compare_face(frame1, frame2): | |
| url = "http://127.0.0.1:8000/api/compare_face" | |
| files = {'image1': open(frame1, 'rb'), 'image2': open(frame2, 'rb')} | |
| r = requests.post(url=url, files=files) | |
| faces = None | |
| try: | |
| image1 = Image.open(frame1) | |
| image2 = Image.open(frame2) | |
| face1 = None | |
| face2 = None | |
| data = r.json().get('data') | |
| if data.get('face1') is not None: | |
| face = data.get('face1') | |
| 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 >= 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))) | |
| if data.get('face2') is not None: | |
| face = data.get('face2') | |
| 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 >= 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( | |
| """ | |
| # Face Recognition | |
| Get your own Face Recognition Server by duplicating this space.<br/> | |
| Or run on your own machine using docker.<br/> | |
| ```docker run -it -p 7860:7860 --platform=linux/amd64 \ | |
| -e LICENSE_KEY="YOUR_VALUE_HERE" \ | |
| registry.hf.space/faceonlive-face-recognition-sdk:latest ```<br/><br/> | |
| Contact us at https://faceonlive.com for issues and support.<br/> | |
| """ | |
| ) | |
| 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) |