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import gradio as gr
import requests
import datadog_api_client
from PIL import Image
def check_liveness(frame):
url = "http://127.0.0.1:8080/check_liveness"
file = {'file': open(frame, 'rb')}
r = requests.post(url=url, files=file)
result = r.json().get('face_state').get('result')
html = None
faces = None
if r.json().get('face_state').get('is_not_front') is not None:
liveness_score = r.json().get('face_state').get('liveness_score')
eye_closed = r.json().get('face_state').get('eye_closed')
is_boundary_face = r.json().get('face_state').get('is_boundary_face')
is_not_front = r.json().get('face_state').get('is_not_front')
is_occluded = r.json().get('face_state').get('is_occluded')
is_small = r.json().get('face_state').get('is_small')
luminance = r.json().get('face_state').get('luminance')
mouth_opened = r.json().get('face_state').get('mouth_opened')
quality = r.json().get('face_state').get('quality')
html = ("<table>"
"<tr>"
"<th>Face State</th>"
"<th>Value</th>"
"</tr>"
"<tr>"
"<td>Result</td>"
"<td>{result}</td>"
"</tr>"
"<tr>"
"<td>Liveness Score</td>"
"<td>{liveness_score}</td>"
"</tr>"
"<tr>"
"<td>Quality</td>"
"<td>{quality}</td>"
"</tr>"
"<tr>"
"<td>Luminance</td>"
"<td>{luminance}</td>"
"</tr>"
"<tr>"
"<td>Is Small</td>"
"<td>{is_small}</td>"
"</tr>"
"<tr>"
"<td>Is Boundary</td>"
"<td>{is_boundary_face}</td>"
"</tr>"
"<tr>"
"<td>Is Not Front</td>"
"<td>{is_not_front}</td>"
"</tr>"
"<tr>"
"<td>Face Occluded</td>"
"<td>{is_occluded}</td>"
"</tr>"
"<tr>"
"<td>Eye Closed</td>"
"<td>{eye_closed}</td>"
"</tr>"
"<tr>"
"<td>Mouth Opened</td>"
"<td>{mouth_opened}</td>"
"</tr>"
"</table>".format(liveness_score=liveness_score, quality=quality, luminance=luminance, is_small=is_small, is_boundary_face=is_boundary_face,
is_not_front=is_not_front, is_occluded=is_occluded, eye_closed=eye_closed, mouth_opened=mouth_opened, result=result))
else:
html = ("<table>"
"<tr>"
"<th>Face State</th>"
"<th>Value</th>"
"</tr>"
"<tr>"
"<td>Result</td>"
"<td>{result}</td>"
"</tr>"
"</table>".format(result=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, html]
def compare_face(frame1, frame2):
url = "http://127.0.0.1:8081/compare_face"
files = {'file1': open(frame1, 'rb'), 'file2': open(frame2, 'rb')}
r = requests.post(url=url, files=files)
html = None
faces = None
compare_result = r.json().get('compare_result')
compare_similarity = r.json().get('compare_similarity')
html = ("<table>"
"<tr>"
"<th>Compare Result</th>"
"<th>Value</th>"
"</tr>"
"<tr>"
"<td>Result</td>"
"<td>{compare_result}</td>"
"</tr>"
"<tr>"
"<td>Similarity</td>"
"<td>{compare_similarity}</td>"
"</tr>"
"</table>".format(compare_result=compare_result, compare_similarity=compare_similarity))
try:
image1 = Image.open(frame1)
image2 = Image.open(frame2)
face1 = None
face2 = None
if r.json().get('face1') is not None:
face = r.json().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 r.json().get('face2') is not None:
face = r.json().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 [faces, html]
def idcard_recognition(frame):
url = "http://127.0.0.1:8082/idcard_recognition"
files = {'file': open(frame, 'rb')}
r = requests.post(url=url, files=files)
html = None
images = None
mrz = None
status = r.json().get('Status')
table_value = ""
if r.json().get('MRZ') is not None:
mrz = r.json().get('MRZ')
for key, value in r.json().items():
if key == 'Status' or key == 'Images' or key == 'MRZ' or key == 'Position':
continue
mrz_value = ''
if mrz is not None and mrz.get(key) is not None:
mrz_value = mrz[key]
del mrz[key]
row_value = ("<tr>"
"<td>{key}</td>"
"<td>{value}</td>"
"<td>{mrz_value}</td>"
"</tr>".format(key=key, value=value, mrz_value=mrz_value))
table_value = table_value + row_value
if mrz is not None:
for key, value in mrz.items():
if key == 'MRZ':
value = value.replace('<', '<')
value = value.replace(',', '<p>')
row_value = ("<tr>"
"<td>{key}</td>"
"<td>{value}</td>"
"<td>{mrz_value}</td>"
"</tr>".format(key=key, value='', mrz_value=value))
table_value = table_value + row_value
html = ("<table>"
"<tr>"
"<th style=""width:20%"">Field</th>"
"<th style=""width:40%"">Value</th>"
"<th style=""width:40%"">MRZ</th>"
"</tr>"
"<tr>"
"<td>Status</td>"
"<td>{status}</td>"
"<td></td>"
"</tr>"
"{table_value}"
"</table>".format(status=status, table_value=table_value))
table_value = ""
for key, value in r.json().items():
if key == 'Images':
for image_key, image_value in value.items():
row_value = ("<tr>"
"<td>{key}</td>"
"<td><img src=""data:image/png;base64,{base64_image} width = '200' height= '100' /></td>"
"</tr>".format(key=image_key, base64_image=image_value))
table_value = table_value + row_value
images = ("<table>"
"<tr>"
"<th>Field</th>"
"<th>Image</th>"
"</tr>"
"{table_value}"
"</table>".format(table_value=table_value))
return [html, images]
with gr.Blocks() as demo:
gr.Markdown(
"""
# KBY-AI Technology
We offer SDKs for face recognition, liveness detection, and ID card recognition.
"""
)
with gr.TabItem("Face Liveness Detection"):
with gr.Row():
with gr.Column():
live_image_input = gr.Image(type='filepath')
gr.Examples(['gradio/live_examples/1.jpg', 'gradio/live_examples/2.jpg', 'gradio/live_examples/3.jpg', 'gradio/live_examples/4.jpg'],
inputs=live_image_input)
check_liveness_button = gr.Button("Check Liveness")
with gr.Column():
liveness_face_output = gr.Image(type="pil").style(height=150)
livness_result_output = gr.HTML()
check_liveness_button.click(check_liveness, inputs=live_image_input, outputs=[liveness_face_output, livness_result_output])
with gr.TabItem("Face Recognition"):
with gr.Row():
with gr.Column():
compare_face_input1 = gr.Image(type='filepath')
gr.Examples(['gradio/face_examples/1.jpg', 'gradio/face_examples/3.jpg', 'gradio/face_examples/5.jpg', 'gradio/face_examples/7.jpg', 'gradio/face_examples/9.jpg'],
inputs=compare_face_input1)
compare_face_button = gr.Button("Compare Face")
with gr.Column():
compare_face_input2 = gr.Image(type='filepath')
gr.Examples(['gradio/face_examples/2.jpg', 'gradio/face_examples/4.jpg', 'gradio/face_examples/6.jpg', 'gradio/face_examples/8.jpg', 'gradio/face_examples/10.jpg'],
inputs=compare_face_input2)
with gr.Column():
compare_face_output = gr.Image(type="pil").style(height=150)
compare_result_output = gr.HTML(label='Result')
compare_face_button.click(compare_face, inputs=[compare_face_input1, compare_face_input2], outputs=[compare_face_output, compare_result_output])
with gr.TabItem("ID Card Recognition"):
with gr.Row():
with gr.Column(scale=3):
id_image_input = gr.Image(type='filepath')
gr.Examples(['gradio/idcard_examples/1.jpg', 'gradio/idcard_examples/2.jpg', 'gradio/idcard_examples/3.jpg'],
inputs=id_image_input)
id_recognition_button = gr.Button("ID Card Recognition")
with gr.Column(scale=5):
id_result_output = gr.HTML()
with gr.Column(scale=2):
image_result_output = gr.HTML()
id_recognition_button.click(idcard_recognition, inputs=id_image_input, outputs=[id_result_output, image_result_output])
demo.launch(server_name="0.0.0.0", server_port=7860) |