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| import os | |
| 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, headers=headers) | |
| faces = None | |
| try: | |
| image1 = Image.open(frame1) | |
| image2 = Image.open(frame2) | |
| face1 = None | |
| face2 = None | |
| res1 = r.json().get('image1') | |
| if res1 is not None: | |
| face = res1.get('detection') | |
| 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))) | |
| res2 = r.json().get('image2') | |
| if res2 is not None: | |
| face = res2.get('detection') | |
| 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(), [face1, face2]] | |
| with gr.Blocks(theme='aliabid94/new-theme') as demo: | |
| ''' | |
| demo.load( | |
| None, | |
| None, | |
| js=""" | |
| () => { | |
| const params = new URLSearchParams(window.location.search); | |
| if (!params.has('__theme')) { | |
| params.set('__theme', 'dark'); | |
| window.location.search = params.toString(); | |
| } | |
| }""", | |
| )''' | |
| with gr.Row(): | |
| with gr.Column(): | |
| compare_face_input1 = gr.Image(label="Image1", type='filepath', height=480) | |
| gr.Examples(['examples/1.jpg', 'examples/2.jpg', 'examples/3.jpg', 'examples/4.jpg'], | |
| inputs=compare_face_input1) | |
| compare_face_button = gr.Button("Face Analysis & Verification", variant="primary") | |
| with gr.Column(): | |
| compare_face_input2 = gr.Image(label="Image2", type='filepath', height=480) | |
| gr.Examples(['examples/5.jpg', 'examples/6.jpg', 'examples/7.jpg', 'examples/8.jpg'], | |
| inputs=compare_face_input2) | |
| with gr.Column(): | |
| compare_face_output = gr.Gallery(label="Faces", height=250, columns=[2], rows=[1]) | |
| 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) |