Update app.py

app.py

@@ -1,214 +1,221 @@
-import sys
-sys.path.append('.')
-
-import os
-import base64
-import json
-from ctypes import *
-import cv2
-import numpy as np
-from flask import Flask, request, jsonify
-from veinsdk import *
-from roi import *
-
-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('/palmvein', methods=['POST'])
-def palmvein():
-    result = None
-    score = None
-    
-    file1 = request.files['file1']
-    file2 = request.files['file2']
-    
-    try:
-        image1 = cv2.imdecode(np.frombuffer(file1.read(), np.uint8), cv2.IMREAD_COLOR)
-    except:
-        result = "Failed to open file1"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    try:
-        image2 = cv2.imdecode(np.frombuffer(file2.read(), np.uint8), cv2.IMREAD_COLOR)
-    except:
-        result = "Failed to open file2"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    roi1, label1 = get_roi_image(cv2.flip(image1, 1))
-    roi2, label2 = get_roi_image(cv2.flip(image2, 1))
-
-    if label1 != label2:
-        result = "2 images are from the different hand"
-        score = 0.0
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-        
-    if roi1 is None or roi2 is None:
-        result = "\n hand detection failed !\n plesae make sure that input hand image is valid or not."
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    roi_byte1 = mat_to_bytes(roi1)
-    roi_byte2 = mat_to_bytes(roi2)
-    feature_array1, feature_array2 = (c_float * 1024)(), (c_float * 1024)()  # Assuming a maximum of 256 rectangles
-    cnt1 = getFeature(roi_byte1, len(roi_byte1), feature_array1)
-    cnt2 = getFeature(roi_byte2, len(roi_byte2), feature_array2)
-
-    if cnt1 == 0 or cnt2 ==0:
-        result = "feature extraction failed !"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    score = getScore(feature_array1, cnt1, feature_array2, cnt2)
-    if score >= 0.65:
-        result = "Same Hand !"
-        # print(f"\n 2 images are from the same hand\n similarity: {score}")
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    else:
-        result = "Different Hand !"
-        # print(f"\n 2 images are from the different hand\n similarity: {score}")
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response    
-
-@app.route('/palmvein_base64', methods=['POST'])
-def palmvein_base64():
-
-    result = None
-    score = None
-    
-    content = request.get_json()
-
-    try:
-        imageBase64 = content['base64_1']
-        image_data = base64.b64decode(imageBase64) 
-        np_array = np.frombuffer(image_data, np.uint8)
-        image1 = cv2.imdecode(np_array, cv2.IMREAD_COLOR)   
-    except:
-        result = "Failed to open file1"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    try:
-        imageBase64 = content['base64_2']
-        image_data = base64.b64decode(imageBase64) 
-        np_array = np.frombuffer(image_data, np.uint8)
-        image2 = cv2.imdecode(np_array, cv2.IMREAD_COLOR)   
-    except:
-        result = "Failed to open file2"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    roi1, label1 = get_roi_image(cv2.flip(image1, 1))
-    roi2, label2 = get_roi_image(cv2.flip(image2, 1))
-
-    if label1 != label2:
-        result = "2 images are from the different hand"
-        score = 0.0
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-        
-    if roi1 is None or roi2 is None:
-        result = "\n hand detection failed !\n plesae make sure that input hand image is valid or not."
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    
-    roi_byte1 = mat_to_bytes(roi1)
-    roi_byte2 = mat_to_bytes(roi2)
-    feature_array1, feature_array2 = (c_float * 1024)(), (c_float * 1024)()  # Assuming a maximum of 256 rectangles
-    cnt1 = getFeature(roi_byte1, len(roi_byte1), feature_array1)
-    cnt2 = getFeature(roi_byte2, len(roi_byte2), feature_array2)
-
-    if cnt1 == 0 or cnt2 ==0:
-        result = "feature extraction failed !"
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-
-    score = getScore(feature_array1, cnt1, feature_array2, cnt2)
-    if score >= 0.65:
-        result = "Same Hand !"
-        # print(f"\n 2 images are from the same hand\n similarity: {score}")
-        response = jsonify({"result": result, "score": float(score)})
-
-        response.status_code = 200
-        response.headers["Content-Type"] = "application/json; charset=utf-8"
-        return response
-    else:
-        result = "Different Hand !"
-        # print(f"\n 2 images are from the different hand\n similarity: {score}")
-        response = jsonify({"result": result, "score": float(score)})
-
-        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 *
+import cv2
+import numpy as np
+from flask import Flask, request, jsonify
+from veinsdk import *
+from roi import *
+
+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('/palmvein', methods=['POST'])
+def palmvein():
+    result = None
+    score = None
+    
+    file1 = request.files['file1']
+    file2 = request.files['file2']
+    
+    try:
+        image1 = cv2.imdecode(np.frombuffer(file1.read(), np.uint8), cv2.IMREAD_COLOR)
+    except:
+        result = "Failed to open file1"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+
+    try:
+        image2 = cv2.imdecode(np.frombuffer(file2.read(), np.uint8), cv2.IMREAD_COLOR)
+    except:
+        result = "Failed to open file2"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    
+    roi1, label1 = get_roi_image(cv2.flip(image1, 1))
+    roi2, label2 = get_roi_image(cv2.flip(image2, 1))
+
+    if label1 != label2:
+        result = "2 images are from the different hand"
+        score = 0.0
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+        
+    if roi1 is None or roi2 is None:
+        result = "\n hand detection failed !\n plesae make sure that input hand image is valid or not."
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    
+    roi_byte1 = mat_to_bytes(roi1)
+    roi_byte2 = mat_to_bytes(roi2)
+    feature_array1, feature_array2 = (c_float * 1024)(), (c_float * 1024)()  # Assuming a maximum of 256 rectangles
+    cnt1 = getFeature(roi_byte1, len(roi_byte1), feature_array1)
+    cnt2 = getFeature(roi_byte2, len(roi_byte2), feature_array2)
+
+    if cnt1 == 0 or cnt2 ==0:
+        result = "feature extraction failed !"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+
+    score = getScore(feature_array1, cnt1, feature_array2, cnt2)
+    if score >= 0.65:
+        result = "Same Hand !"
+        # print(f"\n 2 images are from the same hand\n similarity: {score}")
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    else:
+        result = "Different Hand !"
+        # print(f"\n 2 images are from the different hand\n similarity: {score}")
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response    
+
+@app.route('/palmvein_base64', methods=['POST'])
+def palmvein_base64():
+
+    result = None
+    score = None
+    
+    content = request.get_json()
+
+    try:
+        imageBase64 = content['base64_1']
+        image_data = base64.b64decode(imageBase64) 
+        np_array = np.frombuffer(image_data, np.uint8)
+        image1 = cv2.imdecode(np_array, cv2.IMREAD_COLOR)   
+    except:
+        result = "Failed to open file1"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+
+    try:
+        imageBase64 = content['base64_2']
+        image_data = base64.b64decode(imageBase64) 
+        np_array = np.frombuffer(image_data, np.uint8)
+        image2 = cv2.imdecode(np_array, cv2.IMREAD_COLOR)   
+    except:
+        result = "Failed to open file2"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    
+    roi1, label1 = get_roi_image(cv2.flip(image1, 1))
+    roi2, label2 = get_roi_image(cv2.flip(image2, 1))
+
+    if label1 != label2:
+        result = "2 images are from the different hand"
+        score = 0.0
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+        
+    if roi1 is None or roi2 is None:
+        result = "\n hand detection failed !\n plesae make sure that input hand image is valid or not."
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    
+    roi_byte1 = mat_to_bytes(roi1)
+    roi_byte2 = mat_to_bytes(roi2)
+    feature_array1, feature_array2 = (c_float * 1024)(), (c_float * 1024)()  # Assuming a maximum of 256 rectangles
+    cnt1 = getFeature(roi_byte1, len(roi_byte1), feature_array1)
+    cnt2 = getFeature(roi_byte2, len(roi_byte2), feature_array2)
+
+    if cnt1 == 0 or cnt2 ==0:
+        result = "feature extraction failed !"
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+
+    score = getScore(feature_array1, cnt1, feature_array2, cnt2)
+    if score >= 0.65:
+        result = "Same Hand !"
+        # print(f"\n 2 images are from the same hand\n similarity: {score}")
+        response = jsonify({"result": result, "score": float(score)})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    else:
+        result = "Different Hand !"
+        # print(f"\n 2 images are from the different hand\n similarity: {score}")
+        response = jsonify({"result": result, "score": float(score)})
+
+        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)