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Upload 2 files
Browse files- demo.py +7 -7
- similarity_check.py +15 -32
demo.py
CHANGED
@@ -61,7 +61,7 @@ def get_face_encoding(path):
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# if cv2.waitKey(1) & 0xFF == ord('q'):
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# break
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-
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def process_frame(frame, process_this_frame, face_locations, faces, face_names, score):
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hkid_face_encoding = get_face_encoding("image")
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@@ -84,12 +84,12 @@ def process_frame(frame, process_this_frame, face_locations, faces, face_names,
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# print(f'frame: {len(frame)}')
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# try:
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# small_frame = cv2.imread(image_dir)
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-
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# else:
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# print('fram has nth')
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# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
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rgb_small_frame = cv2.cvtColor(
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(rgb_small_frame)
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@@ -142,10 +142,10 @@ def process_frame(frame, process_this_frame, face_locations, faces, face_names,
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for (top, right, bottom, left), name in zip(face_locations, face_names):
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# Scale back up face locations since the frame we detected in was scaled to 1/4 size
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# Draw a box around the face
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cv2.rectangle(frame, (left, top), (right, bottom), (65, 181, 41), 4)
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# if cv2.waitKey(1) & 0xFF == ord('q'):
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# break
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# frames are the snapshot of the video
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def process_frame(frame, process_this_frame, face_locations, faces, face_names, score):
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hkid_face_encoding = get_face_encoding("image")
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# print(f'frame: {len(frame)}')
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# try:
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# small_frame = cv2.imread(image_dir)
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small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)
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# else:
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# print('fram has nth')
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# Convert the image from BGR color (which OpenCV uses) to RGB color (which face_recognition uses)
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rgb_small_frame = cv2.cvtColor(small_frame, cv2.COLOR_BGR2RGB)
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# Find all the faces and face encodings in the current frame of video
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face_locations = face_recognition.face_locations(rgb_small_frame)
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for (top, right, bottom, left), name in zip(face_locations, face_names):
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# Scale back up face locations since the frame we detected in was scaled to 1/4 size
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top *= 4
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right *= 4
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bottom *= 4
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left *= 4
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# Draw a box around the face
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cv2.rectangle(frame, (left, top), (right, bottom), (65, 181, 41), 4)
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similarity_check.py
CHANGED
@@ -1,10 +1,10 @@
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from
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from model2 import model2
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import checkTool as ct
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import extract_pdf as pf
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import extraction_data as ed
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import get_chinese_name as cn
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import search_engine as se
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# get info from hkid card
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@@ -43,29 +43,19 @@ def get_data(img1_path, img2_path):
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# img_fp = 'IMG_4495.jpg'
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info1 = model1(img1_path)
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info2 = model2(img1_path)
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def print_info(name, valid_hkid, hkid, issuedate):
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cinfo = ct.combine_info(info1, info2)
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# get info from bank
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# images = r'hangseng_page-0001.jpg'
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# bank_list = ['bankofchina','hangsengbank','hsbc','sc']
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# image_path = 'hangseng_page-0001.jpg'
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# post_url = r''
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# name = pf.get_info_from_bank(img2_path)
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# name = pf.check_mr(name)
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# name = name.replace(' ', '')
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# name = name.lower()
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# data = pf.get_info_from_bank(img2_path, file_name)
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data = ed.get_info_from_bank(img2_path)
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name = data["nameStatement"]
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@@ -75,24 +65,17 @@ def get_data(img1_path, img2_path):
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# img_fp = 'IMG_1234.jpg'
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name1 = cinfo[0]
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threshold = 85
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# print(f'Name in HKID: {name1}')
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# print(f'Nmae in bank statement: {name}')
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similarity_score = string_similarity(name,name1)
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# print(f'Similarity: {similarity_score}')
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# if (similarity_score >= threshold): # Above threshold
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# print('It is the same person')
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# else: # Below threshold
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# print('It is not the same person')
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data["similarity_score"] = similarity_score
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data["name_on_id"] = name1
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data["hkid"] = cinfo[2]
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data["validity"] = cinfo[1]
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data["issue_date"] = cinfo[3]
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#
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# chi_name = cn.get_chiname(img1_path)["Chinese Name"]
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chi_name = "allen lau"
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data["chi_name_id"] = chi_name
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return data
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from model0 import model0
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import checkTool as ct
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import extract_pdf as pf
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import extraction_data as ed
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import get_chinese_name as cn
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import search_engine as se
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import get_chinese_code as cc
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# get info from hkid card
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# img_fp = 'IMG_4495.jpg'
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# info1 = model1(img1_path)
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# info2 = model2(img1_path)
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# def print_info(name, valid_hkid, hkid, issuedate):
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# print(f'Name: {name}') # name is without space
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# print(f'HKID: {hkid} and validity: {valid_hkid}')
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# print(f'Date of issue: {issuedate}')
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# cinfo = ct.combine_info(info1, info2)
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cinfo = model0(img1_path)
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print(cinfo)
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# get info from bank
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data = ed.get_info_from_bank(img2_path)
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name = data["nameStatement"]
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# img_fp = 'IMG_1234.jpg'
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name1 = cinfo[0]
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threshold = 85
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similarity_score = string_similarity(name,name1)
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data["similarity_score"] = similarity_score
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data["name_on_id"] = name1
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data["hkid"] = cinfo[2]
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data["validity"] = cinfo[1]
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data["issue_date"] = cinfo[3]
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data["dateofbirth"] = cinfo[4]
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# Get chinese name
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chi_name = cc.get_chinese_name(img1_path)
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# chi_name = cn.get_chiname(img1_path)["Chinese Name"]
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data["chi_name_id"] = chi_name
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return data
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