Update demo.py

demo.py

@@ -1,159 +1,77 @@
-import sys
-sys.path.append('.')
-
-import os
-import base64
-import json
-from ctypes import *
-from alprsdk import initSDK, getLicensePlate, getMachineCode, freeLicenseResults, setActivation
-import cv2
-import numpy as np
-from flask import Flask, request, jsonify
-
-
-licensePath = "license.txt"
-license = ""
-
-machineCode = getMachineCode()
-print("\nmachineCode: ", machineCode.decode('utf-8'))
-
-try:
-    with open(licensePath, 'r') as file:
-        license = file.read().strip()
-except IOError as exc:
-    print("failed to open license.txt: ", exc.errno)
-
-print("\nlicense: ", license)
-
-ret = setActivation(license.encode('utf-8'))
-print("\nactivation: ", ret)
-
-ret = initSDK()
-print("init: ", ret)
-
-app = Flask(__name__) 
-
-def mat_to_bytes(mat):
-    """
-    Convert cv::Mat image data (NumPy array in Python) to raw bytes.
-    """
-    # Encode cv::Mat as PNG bytes
-    is_success, buffer = cv2.imencode(".png", mat)
-    if not is_success:
-        raise ValueError("Failed to encode cv::Mat image")
-    return buffer.tobytes()
-
-@app.route('/alpr', methods=['POST'])
-def alpr():
-    result = "None"
-    license = {}
-    box = {}
-    
-    file = request.files['file']
-    
-    try:
-        image = cv2.imdecode(np.frombuffer(file.read(), np.uint8), cv2.IMREAD_COLOR)
-
-    except:
-        result = "Failed to open file1"
-        response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    
-    img_byte = mat_to_bytes(image)
-    
-    recog_array = (c_int * 1024)()  # Assuming a maximum of 256 rectangles
-    
-    license_plate_ptr = POINTER(c_char_p)()
-    cnt = getLicensePlate(img_byte, len(img_byte), byref(license_plate_ptr), recog_array)
-
-    license_plate = [license_plate_ptr[i].decode('utf-8') for i in range(cnt)]
-    rectangles = [
-    (recog_array[i * 4], recog_array[i * 4 + 1], recog_array[i * 4 + 2], recog_array[i * 4 + 3])
-    for i in range(cnt)]
-
-    freeLicenseResults(license_plate_ptr, cnt)
-    
-    # print("number: ", cnt, rectangles, license_plate)
-    if cnt == 0:
-        result = "Nothing Detected !"
-        response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    result = "License Plate Number Detected !"
-    for i in range(cnt):
-        license[f"vehicle {i + 1}"] = license_plate[i]
-        box[f"vehicle {i + 1}"] = rectangles[i]
-    
-    response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
-
-@app.route('/alpr_base64', methods=['POST'])
-def alpr_base64():
-
-    result = "None"
-    license = {}
-    box = {}
-    
-    content = request.get_json()
-
-    try:
-        imageBase64 = content['base64']
-        image_data = base64.b64decode(imageBase64) 
-        np_array = np.frombuffer(image_data, np.uint8)
-        image = cv2.imdecode(np_array, cv2.IMREAD_COLOR)   
-    except:
-        result = "Failed to open file1"
-        response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-
-    img_byte = mat_to_bytes(image)
-    
-    recog_array = (c_int * 1024)()  # Assuming a maximum of 256 rectangles
-    
-    license_plate_ptr = POINTER(c_char_p)()
-    cnt = getLicensePlate(img_byte, len(img_byte), byref(license_plate_ptr), recog_array)
-
-    license_plate = [license_plate_ptr[i].decode('utf-8') for i in range(cnt)]
-    rectangles = [
-    (recog_array[i * 4], recog_array[i * 4 + 1], recog_array[i * 4 + 2], recog_array[i * 4 + 3])
-    for i in range(cnt)]
-
-    freeLicenseResults(license_plate_ptr, cnt)
-    
-    # print("number: ", cnt, rectangles, license_plate)
-    if cnt == 0:
-        result = "Nothing Detected !"
-        response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    result = "License Plate Number Detected !"
-    for i in range(cnt):
-        license[f"vehicle {i + 1}"] = license_plate[i]
-        box[f"vehicle {i + 1}"] = rectangles[i]
-    
-    response = jsonify({"result": result, "plate number": license, "coordinate": box})
-
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
-
-if __name__ == '__main__':
-    port = int(os.environ.get("PORT", 8080))
-    app.run(host='0.0.0.0', port=port)
+import gradio as gr
+import requests
+from PIL import Image
+import io
+import cv2
+import numpy as np
+
+palmprint_count = 0
+
+def compare_palmprint(frame1, frame2):
+    global palmprint_count
+    
+    palmprint_count = palmprint_count + 1
+
+    url = "http://127.0.0.1:8080/compare_palmprint"
+    files = {'file1': open(frame1, 'rb'), 'file2': open(frame2, 'rb')}
+
+    r = requests.post(url=url, files=files)
+
+    html = 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))
+
+    return [html]
+
+with gr.Blocks() as demo:
+    gr.Markdown(
+        """
+    # KBY-AI License Plate Recognition 
+    We offer SDKs for face recognition, liveness detection(anti-spoofing), ID card recognition and ID document liveness detection. 
+    We also specialize in providing outsourcing services with a variety of technical stacks like AI(Computer Vision/Machine Learning), mobile apps, and web apps.
+    
+    ##### KYC Verification Demo - https://github.com/kby-ai/KYC-Verification-Demo-Android
+    ##### ID Capture Web Demo - https://id-document-recognition-react-alpha.vercel.app
+    """
+    )
+
+    with gr.TabItem("License Plate Recognition"):
+        gr.Markdown(
+            """
+        ##### Docker Hub - https://hub.docker.com/r/kbyai/license-plate-recognition
+        ```bash
+        sudo docker pull kbyai/license-plate-recognition:latest
+        sudo docker run -v ./license.txt:/home/openvino/kby-ai-alpr/license.txt -p 8081:8080 -p 9001:9000 kbyai/license-plate-recognition:latest
+        ```
+        """
+        )
+        with gr.Row():
+            with gr.Column():
+                alpr_image_input = gr.Image(type='filepath', height=300)
+                gr.Examples(['alpr_examples/test1.jpg', 'alpr_examples/test2.jpg', 'alpr_examples/test3.jpg'], 
+                            inputs=alpr_image_input)
+                alpr_confirmation_button = gr.Button("Confirm")
+            with gr.Column():
+                with gr.Column():
+                alpr_output = gr.Image(type="numpy")
+
+        alpr_confirmation_button.click(alpr, inputs=alpr_image_input, outputs=alpr_output)
+    gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fweb.kby-ai.com%2F"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fweb.kby-ai.com%2F&label=VISITORS&countColor=%23263759" /></a>')
+
+demo.launch(server_name="0.0.0.0", server_port=7860)