app.py

import sys
import os
import io
import gradio as gr
import json
import requests
from PIL import Image

css = """
.example-image img{
    display: flex; /* Use flexbox to align items */
    justify-content: center; /* Center the image horizontally */
    align-items: center; /* Center the image vertically */
    height: 300px; /* Set the height of the container */
    object-fit: contain;  /* Preserve aspect ratio while fitting the image within the container */
}
.example-image img{
    display: flex; /* Use flexbox to align items */
    text-align: center;
    justify-content: center; /* Center the image horizontally */
    align-items: center; /* Center the image vertically */
    height: 350px;  /* Set the height of the container */
    object-fit: contain;  /* Preserve aspect ratio while fitting the image within the container */
}
.markdown-success-container {
    background-color: #F6FFED;
    padding: 20px;
    margin: 20px;
    border-radius: 1px;
    border: 2px solid green;
    text-align: center;
}
.markdown-fail-container {
    background-color: #FFF1F0;
    padding: 20px;
    margin: 20px;
    border-radius: 1px;
    border: 2px solid red;
    text-align: center;
}
.block-background {
    # background-color: #202020; /* Set your desired background color */
    border-radius: 5px;
}
"""

screenReplayThreshold = 0.5
portraitReplaceThreshold = 0.5
printedCopyThreshold = 0.5

def find_key_in_dict(d, target_key):
  for key, value in d.items():
    if key == target_key:
      return value
    elif isinstance(value, dict):  # If the value is a dictionary, search recursively
      result = find_key_in_dict(value, target_key)
      if result is not None:
        return result
  return None

def json_to_html_table(data, image_keys):
  html = "<table border='1' style='border-collapse: collapse; width: 100%;'>"
  for key, value in data.items():
    if isinstance(value, dict):
      html += f"<tr><td colspan='2'><strong>{key}</strong></td></tr>"
      for sub_key, sub_value in value.items():
        if sub_key in image_keys:
          html += f"<tr><td>{sub_key}</td><td><img src='data:image/png;base64,{sub_value}' width = '200'  height= '100' /></td></tr>"
        else:
          html += f"<tr><td>{sub_key}</td><td>{sub_value}</td></tr>"
    else:
      if key in image_keys:
        html += f"<tr><td>{key}</td><td><img src='data:image/png;base64,{value}' width = '200'  height= '100' /></td></tr>"
      else:
        html += f"<tr><td>{key}</td><td>{value}</td></tr>"
      
  html += "</table>"
  return html

def check_liveness(frame):
    
  if frame is None:
    liveness_result = f"""<div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Liveness Check Failed</p></div>"""
    return [liveness_result, {"status": "error", "result": "select image file!"}]
  
  img_bytes = io.BytesIO()
  Image.open(frame).save(img_bytes, format="JPEG")
  img_bytes.seek(0)    
  
  url = "https://api.cortex.cerebrium.ai/v4/p-4f1d877e/my-first-project/check-liveness/"
  
  try:
    files = [
          ('file', ('image.jpg', img_bytes, 'image/jpeg'))
      ]

    headers = {
        'Authorization': 'Bearer eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJwcm9qZWN0SWQiOiJwLTRmMWQ4NzdlIiwiaWF0IjoxNzM5MjM2NjA5LCJleHAiOjIwNTQ4MTI2MDl9.0LH0iOnqHZfKTH4GF5iTZ4qNj5vylCryo8rBnErljsq2qD2cpVTetCqhKtnbstTUEjuv6MAJw9jt58z-QNJfYLK9sJcnBhawTR3iM2Ap_bFyjlzg2LbgkwRPjUVJkkcuCRhBKyebXwvqQBvWyOtMq6UekauumbmYBRbA2-T4u343YD4tO2xIfsTsTXznALp1SechjRuys-3xo3ZQbUs05_p38fOFucKI-abc91Eq6sIOkLFjYEM68yuV0UBWl-OSpPu66e0SClroAVlKFDMPS9MY0Jr7X1pBYX4jew6vozj9D8Y-HS-KkdPFqJ7HrZOfQd0wGUgYJHyC58yReWXaRQ',
        # 'Content-Type': 'application/json'
      }
    result = requests.post(url=url, files=files, headers=headers)
  except:
    liveness_result = f"""<div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Liveness Check Failed</p></div>"""
    return [liveness_result, {"status": "error", "result": "failed to open file!"}]
  print("the result is", result)
  if result.ok:
    json_result = result.json()
    if json_result.get("resultCode") == "Error":
      liveness_result = f"""<div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Liveness Check Failed</p></div>"""
      return [liveness_result, {"status": "error", "result": "server error!"}]
    if 'data' in json_result:
        data = json_result['data']
        print("the result data is is",data)
        if data.IsLive :
            liveness_result = f"""<div class="markdown-success-container"><p style="text-align: center; font-size: 20px; color: green;">Liveness Check:  GENUINE</p></div>"""
            json_output = {"Is Live": "Failed" if  data.IsLive else "Success", 
                           "document Type": data.DocumentType,
                           # "Printed Cutout Check": "Failed" if printedCopy < printedCopyThreshold else "Success"
                          }
            # Update json_result with the modified process_results
            return [liveness_result, json_output]
    
    liveness_result = f"""<div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Liveness Check Failed</p></div>"""
    return [liveness_result, {"status": "error", "result": "document not found!"}]
  else:
    liveness_result = f"""<div class="markdown-fail-container"><p style="text-align: center; font-size: 20px; color: red;">Liveness Check Failed</p></div>"""
    return [liveness_result, {"status": "error", "result": f"{result.text}"}]
    
def idcard_recognition(frame1):
  url = "https://api.cortex.cerebrium.ai/v4/p-4f1d877e/my-first-project/process-image/"
  # url = "https://edreesi-ocr-api.hf.space/process-image/"
  
  files = None
  if frame1 is not None:
      # Open the image using Pillow
      img = Image.open(frame1).convert("RGB")  # Convert to RGB to remove alpha channels
      img_bytes = io.BytesIO()
      
      # Save the image in JPEG format with consistent quality
      img.save(img_bytes, format="JPEG", quality=95, optimize=True, exif=b"")  # Strip EXIF metadata
      img_bytes.seek(0)  # Reset the file pointer
      
      # Log the file size for debugging
      print("Gradio File Size:", len(img_bytes.getvalue()), "bytes")
      
      # Prepare the files payload
      files = [
          ('file', ('image.jpg', img_bytes, 'image/jpeg'))
      ]
  else:
      return ['', None, None]
  
#   headers = {"X-RapidAPI-Key": os.environ.get("API_KEY")}
  headers = {}
#   r = requests.post(url=url, files=files, headers=headers)

  # r = requests.request("POST", url, headers=headers, data={}, files=files)
  payload = json.dumps({"prompt": "your value here"})

  headers = {
    'Authorization': 'Bearer eyJhbGciOiJSUzI1NiIsInR5cCI6IkpXVCJ9.eyJwcm9qZWN0SWQiOiJwLTRmMWQ4NzdlIiwiaWF0IjoxNzM5MjM2NjA5LCJleHAiOjIwNTQ4MTI2MDl9.0LH0iOnqHZfKTH4GF5iTZ4qNj5vylCryo8rBnErljsq2qD2cpVTetCqhKtnbstTUEjuv6MAJw9jt58z-QNJfYLK9sJcnBhawTR3iM2Ap_bFyjlzg2LbgkwRPjUVJkkcuCRhBKyebXwvqQBvWyOtMq6UekauumbmYBRbA2-T4u343YD4tO2xIfsTsTXznALp1SechjRuys-3xo3ZQbUs05_p38fOFucKI-abc91Eq6sIOkLFjYEM68yuV0UBWl-OSpPu66e0SClroAVlKFDMPS9MY0Jr7X1pBYX4jew6vozj9D8Y-HS-KkdPFqJ7HrZOfQd0wGUgYJHyC58yReWXaRQ',
    # 'Content-Type': 'application/json'
  }

  r = requests.request("POST", url, headers=headers, data={}, files=files)
  # print(r.text)
  print("Status Code:", r.status_code)
  print("r Body:", r.text)
#   r = requests.post(url=url, files=files, headers=headers)
  print('the result is', r.json())
  images = None   
  rawValues = {}
  image_table_value = ""
  result_table_dict = {
    'portrait':'', 
    'type':'',
    'score':'',
    # 'countryName':'',
    'FullName':'', 
    'Gender':'', 
    'PlaceOfBirth':'', 
    'DateOfBirth':'', 
    'IssuanceCenter':'',
    'IdentityNumber':'',
    'DateOfIssue':'', 
    'DateOfExpiry':'',
    }
  
  if 'data' in r.json():
    data = r.json()['data']
    for key, value in data.items():
        if key == 'faceImage':
            # Assign faceImage to the portrait field
            result_table_dict['portrait'] = value
        elif key == 'barcodeImage':
            # Add barcodeImage to the result dictionary
            result_table_dict['barcodeImage'] = value
        else:
            # Add other fields to the result dictionary
            result_table_dict[key] = value

    # Generate HTML for images
    image_table_value = ""
    if 'barcodeImage' in data:
        image_table_value += (
            "<tr>"
            f"<td>barcodeImage</td>"
            f"<td><img src='data:image/png;base64,{data['barcodeImage']}' width='200' height='100' /></td>"
            "</tr>"
        )

    # Generate the final HTML table for images
    images = (
        "<table>"
        "<tr>"
        "<th>Field</th>"
        "<th>Image</th>"
        "</tr>"
        f"{image_table_value}"
        "</table>"
    )

    # Prepare raw values for JSON output
    for key, value in r.json().items():
        if key == 'data':
            if 'faceImage' in value:
                del value['faceImage']
            if 'barcodeImage' in value:
                del value['barcodeImage']
            rawValues[key] = value
        else:
            rawValues[key] = value

    # Generate the result HTML table
    result = json_to_html_table(result_table_dict, {'portrait', 'barcodeImage'})
    json_result = json.dumps(rawValues, indent=6)
    return [result, json_result, images]
  
def launch_demo():
  with gr.Blocks(css=css) as demo:
    gr.Markdown(
      f"""
      
      <p style="font-size: 20px; font-weight: bold;">📘 Product Documentation</p>
      <div style="display: flex; align-items: center;">          
        &emsp;&emsp;<a href="" style="display: flex; align-items: center;"><img src="https://recognito.vision/wp-content/uploads/2024/05/book.png" style="width: 48px; margin-right: 5px;"/></a>
      </div>
      <p style="font-size: 20px; font-weight: bold;">🏠 Visit Recognito</p>
      
      <br/>
      """
    )

    with gr.Tabs():
      with gr.Tab("ID Document Recognition"):
        with gr.Row():
          with gr.Column(scale=6):
            with gr.Row():
              with gr.Column(scale=6):
                id_image_input1 = gr.Image(type='filepath', label='ID Card Image', elem_classes="example-image")
            #   with gr.Column(scale=3):
            #     id_image_input2 = gr.Image(type='filepath', label='Back', elem_classes="example-image")
            
            # with gr.Row():
              # id_examples = gr.Examples(
              #   examples=[['examples/1_f.png', 'examples/1_b.png'], 
              #             ['examples/2_f.png', 'examples/2_b.png'], 
              #             ['examples/3_f.png', 'examples/3_b.png'], 
              #             ['examples/4.png', None]],
              #   inputs=[id_image_input1, id_image_input1],
              #   outputs=None,
              #   fn=idcard_recognition
              # )
            
          with gr.Blocks():
            with gr.Column(scale=4, min_width=400, elem_classes="block-background"):     
              id_recognition_button = gr.Button("ID Card Recognition", variant="primary", size="lg")

              with gr.Tab("Key Fields"):
                id_result_output = gr.HTML()
              with gr.Tab("Raw JSON"):
                json_result_output = gr.JSON()
              with gr.Tab("Images"):
                image_result_output = gr.HTML()
              
              id_recognition_button.click(idcard_recognition, inputs=id_image_input1, outputs=[id_result_output, json_result_output, image_result_output])

      with gr.Tab("Id Card Liveness Detection"):
        with gr.Row():
          with gr.Column(scale=1):
            id_image_input = gr.Image(label="Image", type='filepath', elem_classes="example-image")
            gr.Examples(examples=['examples/1_f.png', 'examples/2_f.png', 'examples/3_f.png', 'examples/4.png'], inputs=id_image_input)

          with gr.Blocks():
            with gr.Column(scale=1, elem_classes="block-background"):     
              check_liveness_button = gr.Button("Check Document Liveness", variant="primary", size="lg")
              
              liveness_result = gr.Markdown("")
              json_output = gr.JSON()
              
              check_liveness_button.click(check_liveness, inputs=id_image_input, outputs=[liveness_result, json_output])
    
    gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fedreesi-card-recognition.hf.space%2F"><img src="https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Fedreesi-card-recognition.hf.space%2F&countColor=%23263759" /></a>')
    
  demo.launch(server_name="0.0.0.0", server_port=7860, show_api=False)

if __name__ == '__main__':
  launch_demo()