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@@ -10,12 +10,11 @@ RUN rm -rf /var/lib/apt/lists/* && apt update && apt install -y unzip \
     libtbb-dev \
     libopenexr-dev \
     libgl1-mesa-glx \
-    libglib2.0-0 \
-    libgomp1
+    libglib2.0-0
 
 # Set up working directory
-RUN mkdir -p /home/openvino/kby-ai-fire
-WORKDIR /home/openvino/kby-ai-fire
+RUN mkdir -p /home/openvino/kby-ai-alpr
+WORKDIR /home/openvino/kby-ai-alpr
 
 # Copy shared libraries and application files
 COPY ./libopencv.zip .
@@ -24,20 +23,21 @@ RUN cp -f libopencv/* /usr/local/lib/
 RUN ldconfig
 
 # Copy Python and application files
-COPY ./libfire.so .
+COPY ./libalpr.so .
 COPY ./app.py .
-COPY ./firesdk.py .
+COPY ./demo.py .
+COPY ./alprsdk.py .
 COPY ./requirements.txt .
+COPY ./alpr_examples ./alpr_examples
 COPY ./run.sh .
-COPY ./ncnn.zip .
-RUN unzip ncnn.zip
+COPY ./model ./model
 
 # Install Python dependencies
 
 RUN pip3 install --no-cache-dir -r requirements.txt
 # RUN chmod +x ./run.sh
 # USER openvino
-# Set up entrypoint 
+# Set up entrypoint
 CMD ["bash", "./run.sh"]
 
 # Expose ports

app.py

@@ -1,171 +1,175 @@
-import sys
-sys.path.append('.')
-
-import os
-import base64
-import json
-from ctypes import *
-from firesdk import *
-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('/fire', methods=['POST'])
-def fire():
-    result = "None"
-    object_name = {}
-    box = {}
-    pro = {}
-    
-    file = request.files['file']
-    
-    try:
-        image = cv2.imdecode(np.frombuffer(file.read(), np.uint8), cv2.IMREAD_COLOR)
-        # image = cv2.resize(image, (1024, 640))
-    except:
-        result = "Failed to open file"
-        response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    img_byte = mat_to_bytes(image)
-    
-    box_array = (c_int * 1024)()  # Assuming a maximum of 256 rectangles
-    score_array = (c_float * 1024)()  # Assuming a maximum of 256 rectangles
-    label_array = (c_int * 1024)()
-    
-    cnt = getFireDetection(img_byte, len(img_byte), label_array, box_array, score_array)
-
-    rectangles = [
-    (box_array[i * 4], box_array[i * 4 + 1], box_array[i * 4 + 2], box_array[i * 4 + 3])
-    for i in range(cnt)]
-    scores = [score_array[i] for i in range(cnt)]
-    labels = [label_array[i] for i in range(cnt)]
-
-    # print(f"detection number: {cnt}, box: {rectangles}, labels: {labels}, scores: {scores} \n")
-
-    if cnt == 0:
-        result = "Nothing Detected !"
-        response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    result = "Fire or Smoke Detected !"
-    for i in range(cnt):
-        if labels[i] == 0:
-            object_name[f"id {i + 1}"] = "fire"
-        else:
-            object_name[f"id {i + 1}"] = "smoke"
-        box[f"id {i + 1}"] = rectangles[i]
-        pro[f"id {i + 1}"] = scores[i]
-    
-    response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
-
-@app.route('/fire_base64', methods=['POST'])
-def fire_base64():
-
-    result = "None"
-    object_name = {}
-    box = {}
-    pro = {}
-    
-    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)  
-        # image = cv2.resize(image, (1024, 640)) 
-    except:
-        result = "Failed to open file1"
-        response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-
-    img_byte = mat_to_bytes(image)
-    
-    box_array = (c_int * 1024)()  # Assuming a maximum of 256 rectangles
-    score_array = (c_float * 1024)()  # Assuming a maximum of 256 rectangles
-    label_array = (c_int * 1024)()
-    
-    cnt = getFireDetection(img_byte, len(img_byte), label_array, box_array, score_array)
-
-    rectangles = [
-    (box_array[i * 4], box_array[i * 4 + 1], box_array[i * 4 + 2], box_array[i * 4 + 3])
-    for i in range(cnt)]
-    scores = [score_array[i] for i in range(cnt)]
-    labels = [label_array[i] for i in range(cnt)]
-
-    # print(f"detection number: {cnt}, box: {rectangles}, labels: {labels}, scores: {scores} \n")
-
-    if cnt == 0:
-        result = "Nothing Detected !"
-        response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    result = "Fire or Smoke Detected !"
-    for i in range(cnt):
-        if labels[i] == 0:
-            object_name[f"id {i + 1}"] = "fire"
-        else:
-            object_name[f"id {i + 1}"] = "smoke"
-        box[f"id {i + 1}"] = rectangles[i]
-        pro[f"id {i + 1}"] = scores[i]
-    
-    response = jsonify({"result": result, "class": object_name, "coordinate": box, "score": pro})
-
-    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))
+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'))
+
+# Get a specific environment variable by name
+license = os.environ.get("LICENSE")
+
+# Check if the variable exists
+if license is not None:
+    print("Value of LICENSE:")
+else:
+    license = ""
+    try:
+        with open(licensePath, 'r') as file:
+            license = file.read().strip()
+    except IOError as exc:
+        print("failed to open license.txt: ", exc.errno)
+    print("license: ", 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 = {}
+    pro = {}
+    
+    file = request.files['file']
+    
+    try:
+        image = cv2.imdecode(np.frombuffer(file.read(), np.uint8), cv2.IMREAD_COLOR)
+        image = cv2.resize(image, (1024, 640))
+    except:
+        result = "Failed to open file1"
+        response = jsonify({"result": result, "plate number": license, "coordinate": box, "score": pro})
+
+        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
+    score_array = (c_float * 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, score_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)]
+    scores = [score_array[i] 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, "score": pro})
+
+        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]
+        pro[f"vehicle {i + 1}"] = scores[i]
+    
+    response = jsonify({"result": result, "plate number": license, "coordinate": box, "score": pro})
+
+    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 = {}
+    pro = {}
+    
+    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) 
+        image = cv2.resize(image, (1024, 640))
+    except:
+        result = "Failed to open file1"
+        response = jsonify({"result": result, "plate number": license, "coordinate": box, "score": pro})
+
+        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
+    score_array = (c_float * 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)]
+    scores = [score_array[i] 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, "score": pro})
+
+        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]
+        pro[f"vehicle {i + 1}"] = scores[i]
+    
+    response = jsonify({"result": result, "plate number": license, "coordinate": box, "score": pro})
+
+    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)