Update demo.py
Browse files
demo.py
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import os
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import gradio as gr
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import requests
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import json
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import io
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import base64
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import cv2
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import numpy as np
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from gradio.components import Image
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screenReplayThreshold = 0.5
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portraitReplaceThreshold = 0.5
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printedCopyThreshold = 0.5
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def proc_output(result):
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if result.ok:
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json_result = result.json()
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if json_result.get("resultCode") == "Error":
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return {"status": "error", "result": "failed to process image"}
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process_results = json_result.get("result")
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status = process_results.get("status")
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if status == "Ok":
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screenReply = process_results.get("screenReply")
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portraitReplace = process_results.get("portraitReplace")
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printedCopy = process_results.get("printedCopy")
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detResult = "genuine"
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# Check for "Spoof" condition
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if screenReply < screenReplayThreshold or portraitReplace < portraitReplaceThreshold or printedCopy < printedCopyThreshold:
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detResult = "spoof"
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# Update json_result with the modified process_results
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return {"status": "ok", "data": {"result": detResult, "screenreplay_integrity_score": screenReply, "portraitreplace_integrity_score": portraitReplace, "printedcutout_integrity_score": printedCopy}}
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return {"status": "error", "result": "document not found!"}
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else:
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return {"status": "error", "result": result.text}
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def id_liveness(path):
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# Convert PIL image to bytes to send in POST request
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img_bytes = io.BytesIO()
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path.save(img_bytes, format="JPEG")
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img_bytes.seek(0)
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url = "http://127.0.0.1:9000/process_image"
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files = {'image': img_bytes}
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result = requests.post(url=url, files=files)
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return proc_output(result)
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# ID Document Liveness Detection
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Contact us at https://faceonlive.com for issues and support.<br/><br/>
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** For security and privacy, kindly refrain from uploading real ID card or credit card information on this platform.
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"""
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)
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with gr.Row():
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with gr.Column():
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image_input = gr.Image(type='pil')
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gr.Examples(['examples/1.jpg', 'examples/2.jpg', 'examples/3.jpg'],
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inputs=image_input)
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process_button = gr.Button("ID Liveness Detection")
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with gr.Column():
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json_output = gr.JSON()
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process_button.click(id_liveness, inputs=image_input, outputs=[json_output])
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demo.launch(server_name="0.0.0.0")
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import os
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import gradio as gr
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import requests
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import json
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import io
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import base64
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import cv2
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import numpy as np
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from gradio.components import Image
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screenReplayThreshold = 0.5
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portraitReplaceThreshold = 0.5
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printedCopyThreshold = 0.5
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def proc_output(result):
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if result.ok:
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json_result = result.json()
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if json_result.get("resultCode") == "Error":
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return {"status": "error", "result": "failed to process image"}
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process_results = json_result.get("result")
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status = process_results.get("status")
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if status == "Ok":
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screenReply = process_results.get("screenReply")
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portraitReplace = process_results.get("portraitReplace")
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printedCopy = process_results.get("printedCopy")
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detResult = "genuine"
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# Check for "Spoof" condition
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if screenReply < screenReplayThreshold or portraitReplace < portraitReplaceThreshold or printedCopy < printedCopyThreshold:
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detResult = "spoof"
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# Update json_result with the modified process_results
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return {"status": "ok", "data": {"result": detResult, "screenreplay_integrity_score": screenReply, "portraitreplace_integrity_score": portraitReplace, "printedcutout_integrity_score": printedCopy}}
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return {"status": "error", "result": "document not found!"}
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else:
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return {"status": "error", "result": result.text}
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def id_liveness(path):
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# Convert PIL image to bytes to send in POST request
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img_bytes = io.BytesIO()
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path.save(img_bytes, format="JPEG")
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img_bytes.seek(0)
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url = "http://127.0.0.1:9000/process_image"
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files = {'image': img_bytes}
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result = requests.post(url=url, files=files)
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return proc_output(result)
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with gr.Blocks() as demo:
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gr.Markdown(
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"""
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# ID Document Liveness Detection
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Contact us at https://faceonlive.com for issues and support.<br/><br/>
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** For security and privacy, kindly refrain from uploading real ID card or credit card information on this platform.
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"""
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)
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with gr.Row():
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with gr.Column():
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image_input = gr.Image(type='pil')
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gr.Examples(['examples/1.jpg', 'examples/2.jpg', 'examples/3.jpg'],
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inputs=image_input)
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process_button = gr.Button("ID Liveness Detection")
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with gr.Column():
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json_output = gr.JSON()
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process_button.click(id_liveness, inputs=image_input, outputs=[json_output], api_name=False)
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demo.queue(api_open=False).launch(server_name="0.0.0.0", show_api=False)
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