import os
import gradio as gr
import requests
import json
from PIL import Image
def get_attributes(json):
liveness = "GENUINE" if json.get('liveness') >= 0.5 else "FAKE"
attr = json.get('attribute')
age = attr.get('age')
gender = attr.get('gender')
emotion = attr.get('emotion')
ethnicity = attr.get('ethnicity')
mask = [attr.get('face_mask')]
if attr.get('glasses') == 'USUAL':
mask.append('GLASSES')
if attr.get('glasses') == 'DARK':
mask.append('SUNGLASSES')
eye = []
if attr.get('eye_left') >= 0.3:
eye.append('LEFT')
if attr.get('eye_right') >= 0.3:
eye.append('RIGHT')
facehair = attr.get('facial_hair')
haircolor = attr.get('hair_color')
hairtype = attr.get('hair_type')
headwear = attr.get('headwear')
activity = []
if attr.get('food_consumption') >= 0.5:
activity.append('EATING')
if attr.get('phone_recording') >= 0.5:
activity.append('PHONE_RECORDING')
if attr.get('phone_use') >= 0.5:
activity.append('PHONE_USE')
if attr.get('seatbelt') >= 0.5:
activity.append('SEATBELT')
if attr.get('smoking') >= 0.5:
activity.append('SMOKING')
pitch = attr.get('pitch')
roll = attr.get('roll')
yaw = attr.get('yaw')
quality = attr.get('quality')
return liveness, age, gender, emotion, ethnicity, mask, eye, facehair, haircolor, hairtype, headwear, activity, pitch, roll, yaw, quality
def compare_face(frame1, frame2):
url = "https://recognito.p.rapidapi.com/api/face"
try:
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)
except:
raise gr.Error("Please select images files!")
faces = None
try:
image1 = Image.open(frame1)
image2 = Image.open(frame2)
face1 = Image.new('RGBA',(150, 150), (80,80,80,0))
face2 = Image.new('RGBA',(150, 150), (80,80,80,0))
liveness1, age1, gender1, emotion1, ethnicity1, mask1, eye1, facehair1, haircolor1, hairtype1, headwear1, activity1, pitch1, roll1, yaw1, quality1 = [None] * 16
liveness2, age2, gender2, emotion2, ethnicity2, mask2, eye2, facehair2, haircolor2, hairtype2, headwear2, activity2, pitch2, roll2, yaw2, quality2 = [None] * 16
res1 = r.json().get('image1')
if res1 is not None and res1:
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)))
liveness1, age1, gender1, emotion1, ethnicity1, mask1, eye1, facehair1, haircolor1, hairtype1, headwear1, activity1, pitch1, roll1, yaw1, quality1 = get_attributes(res1)
res2 = r.json().get('image2')
if res2 is not None and res2:
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)))
liveness2, age2, gender2, emotion2, ethnicity2, mask2, eye2, facehair2, haircolor2, hairtype2, headwear2, activity2, pitch2, roll2, yaw2, quality2 = get_attributes(res2)
except:
pass
matching_result = ""
if face1 is not None and face2 is not None:
matching_score = r.json().get('matching_score')
if matching_score is not None:
matching_result = """<br/><br/><br/><h1 style="text-align: center;color: #05ee3c;">SAME<br/>PERSON</h1>""" if matching_score >= 0.7 else """<br/><br/><br/><h1 style="text-align: center;color: red;">DIFFERENT<br/>PERSON</h1>"""
return [r.json(), [face1, face2], matching_result,
liveness1, age1, gender1, emotion1, ethnicity1, mask1, eye1, facehair1, haircolor1, hairtype1, headwear1, activity1, pitch1, roll1, yaw1, quality1,
liveness2, age2, gender2, emotion2, ethnicity2, mask2, eye2, facehair2, haircolor2, hairtype2, headwear2, activity2, pitch2, roll2, yaw2, quality2]
with gr.Blocks() as demo:
gr.Markdown(
"""
# **Recognito Face Analysis**
## NIST FRVT Top #1 Face Recognition Algorithm Developer<br/>
## Contact us at https://recognito.vision
<img src="https://recognito.vision/wp-content/uploads/2023/12/black-1.png" alt="NIST FRVT 1:1 Leaderboard" width="50%">
"""
)
with gr.Row():
with gr.Column(scale=1):
compare_face_input1 = gr.Image(label="Image1", type='filepath', height=270)
gr.Examples(['examples/1.jpg', 'examples/2.jpg', 'examples/3.jpg', 'examples/4.jpg'],
inputs=compare_face_input1)
compare_face_input2 = gr.Image(label="Image2", type='filepath', height=270)
gr.Examples(['examples/5.jpg', 'examples/6.jpg', 'examples/7.jpg', 'examples/8.jpg'],
inputs=compare_face_input2)
compare_face_button = gr.Button("Face Analysis & Verification", variant="primary", size="lg")
with gr.Column(scale=2):
with gr.Row():
compare_face_output = gr.Gallery(label="Faces", height=230, columns=[2], rows=[1])
with gr.Column(variant="panel"):
compare_result = gr.Markdown("")
with gr.Row():
with gr.Column(variant="panel"):
gr.Markdown("<b>Image 1<b/>")
liveness1 = gr.CheckboxGroup(["GENUINE", "FAKE"], label="Liveness")
age1 = gr.Number(0, label="Age")
gender1 = gr.CheckboxGroup(["MALE", "FEMALE"], label="Gender")
emotion1 = gr.CheckboxGroup(["HAPPINESS", "ANGER", "FEAR", "NEUTRAL", "SADNESS", "SURPRISE"], label="Emotion")
ethnicity1 = gr.CheckboxGroup(["ASIAN", "BLACK", "CAUCASIAN", "EAST_INDIAN"], label="Ethnicity")
mask1 = gr.CheckboxGroup(["LOWER_FACE_MASK", "FULL_FACE_MASK", "OTHER_MASK", "GLASSES", "SUNGLASSES"], label="Mask & Glasses")
eye1 = gr.CheckboxGroup(["LEFT", "RIGHT"], label="Eye Open")
facehair1 = gr.CheckboxGroup(["BEARD", "BRISTLE", "MUSTACHE", "SHAVED"], label="Facial Hair")
haircolor1 = gr.CheckboxGroup(["BLACK", "BLOND", "BROWN"], label="Hair Color")
hairtype1 = gr.CheckboxGroup(["BALD", "SHORT", "MEDIUM", "LONG"], label="Hair Type")
headwear1 = gr.CheckboxGroup(["B_CAP", "CAP", "HAT", "HELMET", "HOOD"], label="Head Wear")
activity1 = gr.CheckboxGroup(["EATING", "PHONE_RECORDING", "PHONE_USE", "SMOKING", "SEATBELT"], label="Activity")
with gr.Row():
pitch1 = gr.Number(0, label="Pitch")
roll1 = gr.Number(0, label="Roll")
yaw1 = gr.Number(0, label="Yaw")
quality1 = gr.Number(0, label="Quality")
with gr.Column(variant="panel"):
gr.Markdown("<b>Image 2<b/>")
liveness2 = gr.CheckboxGroup(["GENUINE", "FAKE"], label="Liveness")
age2 = gr.Number(0, label="Age")
gender2 = gr.CheckboxGroup(["MALE", "FEMALE"], label="Gender")
emotion2 = gr.CheckboxGroup(["HAPPINESS", "ANGER", "FEAR", "NEUTRAL", "SADNESS", "SURPRISE"], label="Emotion")
ethnicity2 = gr.CheckboxGroup(["ASIAN", "BLACK", "CAUCASIAN", "EAST_INDIAN"], label="Ethnicity")
mask2 = gr.CheckboxGroup(["LOWER_FACE_MASK", "FULL_FACE_MASK", "OTHER_MASK", "GLASSES", "SUNGLASSES"], label="Mask & Glasses")
eye2 = gr.CheckboxGroup(["LEFT", "RIGHT"], label="Eye Open")
facehair2 = gr.CheckboxGroup(["BEARD", "BRISTLE", "MUSTACHE", "SHAVED"], label="Facial Hair")
haircolor2 = gr.CheckboxGroup(["BLACK", "BLOND", "BROWN"], label="Hair Color")
hairtype2 = gr.CheckboxGroup(["BALD", "SHORT", "MEDIUM", "LONG"], label="Hair Type")
headwear2 = gr.CheckboxGroup(["B_CAP", "CAP", "HAT", "HELMET", "HOOD"], label="Head Wear")
activity2 = gr.CheckboxGroup(["EATING", "PHONE_RECORDING", "PHONE_USE", "SMOKING", "SEATBELT"], label="Activity")
with gr.Row():
pitch2 = gr.Number(0, label="Pitch")
roll2 = gr.Number(0, label="Roll")
yaw2 = gr.Number(0, label="Yaw")
quality2 = gr.Number(0, label="Quality")
compare_result_output = gr.JSON(label='Result', visible=False)
compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_result_output, compare_face_output, compare_result,
liveness1, age1, gender1, emotion1, ethnicity1, mask1, eye1, facehair1, haircolor1, hairtype1, headwear1, activity1, pitch1, roll1, yaw1, quality1,
liveness2, age2, gender2, emotion2, ethnicity2, mask2, eye2, facehair2, haircolor2, hairtype2, headwear2, activity2, pitch2, roll2, yaw2, quality2])
gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FRecognito%2FFaceAnalysis"><img src="https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FRecognito%2FFaceAnalysis&countColor=%2337d67a&style=flat&labelStyle=upper" /></a>')
demo.launch(server_name="0.0.0.0", server_port=7860, show_api=False)