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.gitattributes

@@ -34,3 +34,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 libfacesdk2.so filter=lfs diff=lfs merge=lfs -text
+libkbyai_facesdk2.so filter=lfs diff=lfs merge=lfs -text

app.py

@@ -16,9 +16,7 @@ from facesdk import templateExtraction
 from facesdk import similarityCalculation
 from facebox import FaceBox
 
-verifyThreshold = 0.67
-
-maxFaceCount = 1
+maxFaceCount = 8
 
 licensePath = "license.txt"
 license = ""
@@ -52,11 +50,6 @@ app = Flask(__name__)
 
 @app.route('/compare_face', methods=['POST'])
 def compare_face():
-    result = "None"
-    similarity = -1
-    face1 = None
-    face2 = None
-
     file1 = request.files['file1']
     file2 = request.files['file2']
 
@@ -64,7 +57,7 @@ def compare_face():
         image1 = Image.open(file1).convert('RGB')
     except:
         result = "Failed to open file1"
-        response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+        response = jsonify({"resultCode": result})
 
         response.status_code = 200
         response.headers["Content-Type"] = "application/json; charset=utf-8"
@@ -75,7 +68,7 @@ def compare_face():
         image2 = Image.open(file2).convert('RGB')
     except:
         result = "Failed to open file2"
-        response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+        response = jsonify({"resultCode": result})
 
         response.status_code = 200
         response.headers["Content-Type"] = "application/json; charset=utf-8"
@@ -90,56 +83,71 @@ def compare_face():
     faceBoxes2 = (FaceBox * maxFaceCount)()
     faceCount2 = faceDetection(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2, maxFaceCount)
 
-    if faceCount1 == 1 and faceCount2 == 1:
-        templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[0])
-        templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[0])
-        similarity = similarityCalculation(faceBoxes1[0].templates, faceBoxes2[0].templates)
-        if similarity > verifyThreshold:
-            result = "Same person"
-        else:
-            result = "Different person"
-    elif faceCount1 == 0:
-        result = "No face1"
-    elif faceCount2 == 0:
-        result = "No face2"
+    faces1_result = []
+    faces2_result = []
+    for i in range(faceCount1):
+        templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[i])
 
-    if faceCount1 == 1:
         landmark_68 = []
         for j in range(68):
-            landmark_68.append({"x": faceBoxes1[0].landmark_68[j * 2], "y": faceBoxes1[0].landmark_68[j * 2 + 1]})
+            landmark_68.append({"x": faceBoxes1[i].landmark_68[j * 2], "y": faceBoxes1[i].landmark_68[j * 2 + 1]})
 
-        face1 = {"x1": faceBoxes1[0].x1, "y1": faceBoxes1[0].y1, "x2": faceBoxes1[0].x2, "y2": faceBoxes1[0].y2, 
-                      "yaw": faceBoxes1[0].yaw, "roll": faceBoxes1[0].roll, "pitch": faceBoxes1[0].pitch,
-                      "face_quality": faceBoxes1[0].face_quality, "face_luminance": faceBoxes1[0].face_luminance, "eye_dist": faceBoxes1[0].eye_dist,
-                      "left_eye_closed": faceBoxes1[0].left_eye_closed, "right_eye_closed": faceBoxes1[0].right_eye_closed,
-                      "face_occlusion": faceBoxes1[0].face_occlusion, "mouth_opened": faceBoxes1[0].mouth_opened,
+        face = {"x1": faceBoxes1[i].x1, "y1": faceBoxes1[i].y1, "x2": faceBoxes1[i].x2, "y2": faceBoxes1[i].y2, 
+                      "yaw": faceBoxes1[i].yaw, "roll": faceBoxes1[i].roll, "pitch": faceBoxes1[i].pitch,
+                      "face_quality": faceBoxes1[i].face_quality, "face_luminance": faceBoxes1[i].face_luminance, "eye_dist": faceBoxes1[i].eye_dist,
+                      "left_eye_closed": faceBoxes1[i].left_eye_closed, "right_eye_closed": faceBoxes1[i].right_eye_closed,
+                      "face_occlusion": faceBoxes1[i].face_occlusion, "mouth_opened": faceBoxes1[i].mouth_opened,
                       "landmark_68": landmark_68}
+        
+        faces1_result.append(face)
+
+    for i in range(faceCount2):
+        templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[i])
 
-    if faceCount2 == 1:
         landmark_68 = []
         for j in range(68):
-            landmark_68.append({"x": faceBoxes2[0].landmark_68[j * 2], "y": faceBoxes2[0].landmark_68[j * 2 + 1]})
+            landmark_68.append({"x": faceBoxes2[i].landmark_68[j * 2], "y": faceBoxes2[i].landmark_68[j * 2 + 1]})
+
 
-        face2 = {"x1": faceBoxes2[0].x1, "y1": faceBoxes2[0].y1, "x2": faceBoxes2[0].x2, "y2": faceBoxes2[0].y2, 
-                      "yaw": faceBoxes2[0].yaw, "roll": faceBoxes2[0].roll, "pitch": faceBoxes2[0].pitch,
-                      "face_quality": faceBoxes2[0].face_quality, "face_luminance": faceBoxes2[0].face_luminance, "eye_dist": faceBoxes2[0].eye_dist,
-                      "left_eye_closed": faceBoxes2[0].left_eye_closed, "right_eye_closed": faceBoxes2[0].right_eye_closed,
-                      "face_occlusion": faceBoxes2[0].face_occlusion, "mouth_opened": faceBoxes2[0].mouth_opened,
+        face = {"x1": faceBoxes2[i].x1, "y1": faceBoxes2[i].y1, "x2": faceBoxes2[i].x2, "y2": faceBoxes2[i].y2, 
+                      "yaw": faceBoxes2[i].yaw, "roll": faceBoxes2[i].roll, "pitch": faceBoxes2[i].pitch,
+                      "face_quality": faceBoxes2[i].face_quality, "face_luminance": faceBoxes2[i].face_luminance, "eye_dist": faceBoxes2[i].eye_dist,
+                      "left_eye_closed": faceBoxes2[i].left_eye_closed, "right_eye_closed": faceBoxes2[i].right_eye_closed,
+                      "face_occlusion": faceBoxes2[i].face_occlusion, "mouth_opened": faceBoxes2[i].mouth_opened,
                       "landmark_68": landmark_68}
+        
+        faces2_result.append(face)
+
+    
+    if faceCount1 > 0 and faceCount2 > 0:
+        results = []
+        for i in range(faceCount1):
+            for j in range(faceCount2): 
+                similarity = similarityCalculation(faceBoxes1[i].templates, faceBoxes2[j].templates)
+                match_result = {"face1": i, "face2": j, "similarity": similarity}
+                results.append(match_result)
+
+        response = jsonify({"resultCode": "Ok", "faces1": faces1_result, "faces2": faces2_result, "results": results})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    elif faceCount1 == 0:
+        response = jsonify({"resultCode": "No face1", "faces1": faces1_result, "faces2": faces2_result})
 
-    response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    elif faceCount2 == 0:
+        response = jsonify({"resultCode": "No face2", "faces1": faces1_result, "faces2": faces2_result})
 
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
 
+        
 @app.route('/compare_face_base64', methods=['POST'])
 def compare_face_base64():
-    result = "None"
-    similarity = -1
-    face1 = None
-    face2 = None
-
     content = request.get_json()
 
     try:
@@ -148,7 +156,7 @@ def compare_face_base64():
         image1 = Image.open(io.BytesIO(image_data1)).convert('RGB')
     except:
         result = "Failed to open file1"
-        response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+        response = jsonify({"resultCode": result})
 
         response.status_code = 200
         response.headers["Content-Type"] = "application/json; charset=utf-8"
@@ -159,8 +167,8 @@ def compare_face_base64():
         image_data2 = base64.b64decode(imageBase64_2)
         image2 = Image.open(io.BytesIO(image_data2)).convert('RGB')
     except IOError as exc:
-        result = "Failed to open file2"
-        response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+        result = "Failed to open file1"
+        response = jsonify({"resultCode": result})
 
         response.status_code = 200
         response.headers["Content-Type"] = "application/json; charset=utf-8"
@@ -175,48 +183,67 @@ def compare_face_base64():
     faceBoxes2 = (FaceBox * maxFaceCount)()
     faceCount2 = faceDetection(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2, maxFaceCount)
 
-    if faceCount1 == 1 and faceCount2 == 1:
-        templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[0])
-        templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[0])
-        similarity = similarityCalculation(faceBoxes1[0].templates, faceBoxes2[0].templates)
-        if similarity > verifyThreshold:
-            result = "Same person"
-        else:
-            result = "Different person"
-    elif faceCount1 == 0:
-        result = "No face1"
-    elif faceCount2 == 0:
-        result = "No face2"
+    faces1_result = []
+    faces2_result = []
+    for i in range(faceCount1):
+        templateExtraction(image_np1, image_np1.shape[1], image_np1.shape[0], faceBoxes1[i])
 
-    if faceCount1 == 1:
         landmark_68 = []
         for j in range(68):
-            landmark_68.append({"x": faceBoxes1[0].landmark_68[j * 2], "y": faceBoxes1[0].landmark_68[j * 2 + 1]})
+            landmark_68.append({"x": faceBoxes1[i].landmark_68[j * 2], "y": faceBoxes1[i].landmark_68[j * 2 + 1]})
 
-        face1 = {"x1": faceBoxes1[0].x1, "y1": faceBoxes1[0].y1, "x2": faceBoxes1[0].x2, "y2": faceBoxes1[0].y2, 
-                      "yaw": faceBoxes1[0].yaw, "roll": faceBoxes1[0].roll, "pitch": faceBoxes1[0].pitch,
-                      "face_quality": faceBoxes1[0].face_quality, "face_luminance": faceBoxes1[0].face_luminance, "eye_dist": faceBoxes1[0].eye_dist,
-                      "left_eye_closed": faceBoxes1[0].left_eye_closed, "right_eye_closed": faceBoxes1[0].right_eye_closed,
-                      "face_occlusion": faceBoxes1[0].face_occlusion, "mouth_opened": faceBoxes1[0].mouth_opened,
+        face = {"x1": faceBoxes1[i].x1, "y1": faceBoxes1[i].y1, "x2": faceBoxes1[i].x2, "y2": faceBoxes1[i].y2, 
+                      "yaw": faceBoxes1[i].yaw, "roll": faceBoxes1[i].roll, "pitch": faceBoxes1[i].pitch,
+                      "face_quality": faceBoxes1[i].face_quality, "face_luminance": faceBoxes1[i].face_luminance, "eye_dist": faceBoxes1[i].eye_dist,
+                      "left_eye_closed": faceBoxes1[i].left_eye_closed, "right_eye_closed": faceBoxes1[i].right_eye_closed,
+                      "face_occlusion": faceBoxes1[i].face_occlusion, "mouth_opened": faceBoxes1[i].mouth_opened,
                       "landmark_68": landmark_68}
+        
+        faces1_result.append(face)
+
+    for i in range(faceCount2):
+        templateExtraction(image_np2, image_np2.shape[1], image_np2.shape[0], faceBoxes2[i])
 
-    if faceCount2 == 1:
         landmark_68 = []
         for j in range(68):
-            landmark_68.append({"x": faceBoxes2[0].landmark_68[j * 2], "y": faceBoxes2[0].landmark_68[j * 2 + 1]})
+            landmark_68.append({"x": faceBoxes2[i].landmark_68[j * 2], "y": faceBoxes2[i].landmark_68[j * 2 + 1]})
+
 
-        face2 = {"x1": faceBoxes2[0].x1, "y1": faceBoxes2[0].y1, "x2": faceBoxes2[0].x2, "y2": faceBoxes2[0].y2, 
-                      "yaw": faceBoxes2[0].yaw, "roll": faceBoxes2[0].roll, "pitch": faceBoxes2[0].pitch,
-                      "face_quality": faceBoxes2[0].face_quality, "face_luminance": faceBoxes2[0].face_luminance, "eye_dist": faceBoxes2[0].eye_dist,
-                      "left_eye_closed": faceBoxes2[0].left_eye_closed, "right_eye_closed": faceBoxes2[0].right_eye_closed,
-                      "face_occlusion": faceBoxes2[0].face_occlusion, "mouth_opened": faceBoxes2[0].mouth_opened,
+        face = {"x1": faceBoxes2[i].x1, "y1": faceBoxes2[i].y1, "x2": faceBoxes2[i].x2, "y2": faceBoxes2[i].y2, 
+                      "yaw": faceBoxes2[i].yaw, "roll": faceBoxes2[i].roll, "pitch": faceBoxes2[i].pitch,
+                      "face_quality": faceBoxes2[i].face_quality, "face_luminance": faceBoxes2[i].face_luminance, "eye_dist": faceBoxes2[i].eye_dist,
+                      "left_eye_closed": faceBoxes2[i].left_eye_closed, "right_eye_closed": faceBoxes2[i].right_eye_closed,
+                      "face_occlusion": faceBoxes2[i].face_occlusion, "mouth_opened": faceBoxes2[i].mouth_opened,
                       "landmark_68": landmark_68}
+        
+        faces2_result.append(face)
 
-    response = jsonify({"compare_result": result, "compare_similarity": similarity, "face1": face1, "face2": face2})
+    
+    if faceCount1 > 0 and faceCount2 > 0:
+        results = []
+        for i in range(faceCount1):
+            for j in range(faceCount2): 
+                similarity = similarityCalculation(faceBoxes1[i].templates, faceBoxes2[j].templates)
+                match_result = {"face1": i, "face2": j, "similarity": similarity}
+                results.append(match_result)
+
+        response = jsonify({"resultCode": "Ok", "faces1": faces1_result, "faces2": faces2_result, "results": results})
 
-    response.status_code = 200
-    response.headers["Content-Type"] = "application/json; charset=utf-8"
-    return response
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    elif faceCount1 == 0:
+        response = jsonify({"resultCode": "No face1", "faces1": faces1_result, "faces2": faces2_result})
+
+        response.status_code = 200
+        response.headers["Content-Type"] = "application/json; charset=utf-8"
+        return response
+    elif faceCount2 == 0:
+        response = jsonify({"resultCode": "No face2", "faces1": faces1_result, "faces2": faces2_result})
+
+        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))

facesdk.py

@@ -4,29 +4,29 @@ from ctypes import *
 from numpy.ctypeslib import ndpointer
 from facebox import FaceBox
 
-libPath = os.path.abspath(os.path.dirname(__file__)) + '/libfacesdk2.so'
+libPath = os.path.abspath(os.path.dirname(__file__)) + '/libkbyai_facesdk2.so'
 facesdk = cdll.LoadLibrary(libPath)
 
-getMachineCode = facesdk.getMachineCode
+getMachineCode = facesdk.kbyai_getMachineCode
 getMachineCode.argtypes = []
 getMachineCode.restype = c_char_p
 
-setActivation = facesdk.setActivation
+setActivation = facesdk.kbyai_setActivation
 setActivation.argtypes = [c_char_p]
 setActivation.restype = c_int32
 
-initSDK = facesdk.initSDK
+initSDK = facesdk.kbyai_initSDK
 initSDK.argtypes = [c_char_p]
 initSDK.restype = c_int32
 
-faceDetection = facesdk.faceDetection
+faceDetection = facesdk.kbyai_faceDetection
 faceDetection.argtypes = [ndpointer(c_ubyte, flags='C_CONTIGUOUS'), c_int32, c_int32, POINTER(FaceBox), c_int32]
 faceDetection.restype = c_int32
 
-templateExtraction = facesdk.templateExtraction
+templateExtraction = facesdk.kbyai_templateExtraction
 templateExtraction.argtypes = [ndpointer(c_ubyte, flags='C_CONTIGUOUS'), c_int32, c_int32, POINTER(FaceBox)]
 templateExtraction.restype = c_int32
 
-similarityCalculation = facesdk.similarityCalculation
+similarityCalculation = facesdk.kbyai_similarityCalculation
 similarityCalculation.argtypes = [c_ubyte * 2048, c_ubyte * 2048]
 similarityCalculation.restype = c_float

libkbyai_facesdk2.so

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:44639279d342cb505feebaf9d2180ffe92d8dfe1886cea510e021dcee222e49e
+size 4942024