import streamlit as st import similarity_check as sc import cv2 from PIL import Image import numpy as np import demo import streamlit as st import request_json.sbt_request_generator as sbt import check_hkid_validity as chv import search_engine as se import socket import pickle from streamlit_webrtc import webrtc_streamer, VideoTransformerBase, RTCConfiguration, WebRtcMode class WebcamTransformer(VideoTransformerBase): def __init__(self): self.frame_count = 0 def transform(self, frame): self.frame_count += 1 return frame def main(): # st.title("SBT Web Application") # today's date = get_today_date # global data html_temp = """

SBT Web Application

""" st.markdown(html_temp, unsafe_allow_html=True) if 'hkid_image_validity' not in st.session_state: st.session_state.hkid_image_validity = False if 'data' not in st.session_state: st.session_state['data'] = {} st.header("I. Similarity Check") image_file = st.file_uploader("Upload Image", type=['jpg', 'png', 'jpeg', 'pdf'], accept_multiple_files=True) if len(image_file) == 1: image1 = Image.open(image_file[0]) st.text("HKID card") st.image(image1) image1.save('image/hkid.jpg', 'JPEG') if chv.check_hkid('image/hkid.jpg'): st.text("Valid HKID card.") st.session_state.hkid_image_validity = True else: st.text("Invalid HKID card. Please upload again!") st.session_state.hkid_image_validity = False elif len(image_file) == 2: image1 = Image.open(image_file[0]) st.text("HKID card") st.image(image1) image2 = Image.open(image_file[1]) # image2 = image_file[1] # image2.save('image/hkid.jpg', 'JPEG') # file_name = image_file[1].name st.text("Bank statement") st.image(image2) print(f"the id is: {st.session_state.hkid_image_validity}") # if image_file2 is not None: # image2 = Image.open(image_file) # st.text("Bank statement") # st.image(image2) # path1 = 'IMG_4495.jpg' # path2 = 'hangseng_page-0001.jpg' # image1 = save_image(image1) # image2 = save_image(image2) data = {} if st.button("Recognise"): with st.spinner('Wait for it...'): # global data data = sc.get_data(image1, image2) # se.get_data_link(data['chi_name_id'], data["name_on_id"], data["address"]) if 'data' in st.session_state: st.session_state['data'] = data st.success('Done!') score = int(st.session_state['data']['similarity_score']) st.text(f'score: {score}') if (score>85): st.text(f'matched') else: st.text(f'unmatched') data = st.session_state['data'] st.header("IIa. HKID Data Extraction") st.text(f'English Name: {data["name_on_id"]}') # name is without space st.text(f'Chinese Name: {data["chi_name_id"]}') # name is without space st.text(f'HKID: {data["hkid"]} and validity: {data["validity"]}') st.text(f'Date of issue: {data["issue_date"]}') st.header("IIb. Bank Statement Data Extraction") st.text(f'Name: {data["nameStatement"]}') st.text(f'Address: {data["address"]}') st.text(f'Bank: {data["bank"]}') st.text(f'Date: {data["statementDate"]}') st.text(f'Asset: {data["totalAsset"]} hkd') st.text(f'Liabilities: {data["totalLiability"]} hkd') if 'data' in st.session_state: tempout = st.session_state['data'] print(f'hello: {tempout}') st.header("II. Facial Recognition") run = st.checkbox('Run') # webrtc_streamer(key="example") # 1. Web Rtc # webrtc_streamer(key="jhv", video_frame_callback=video_frame_callback) # # init the camera face_locations = [] # face_encodings = [] face_names = [] process_this_frame = True score = [] faces = 0 FRAME_WINDOW = st.image([]) # server_ip = "127.0.0.1" # server_port = 6666 # camera = cv2.VideoCapture(1) # s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM) # s.setsockopt(socket.SOL_SOCKET, socket.SO_SNDBUF, 1000000) while run: rtc_configuration = RTCConfiguration({"iceServers": [{"urls": ["stun:stun.l.google.com:19302"]}]}) # Capture frame-by-frame # Grab a single frame of video # ret, frame = camera.read() # Initialize the WebRTC streaming webrtc_ctx = webrtc_streamer( key="face_rec", mode=WebRtcMode.SENDRECV, rtc_configuration=rtc_configuration, video_transformer_factory=WebcamTransformer, media_stream_constraints={"video": True, "audio": False}, async_processing=True, ) if webrtc_ctx.video_transformer: st.header("Webcam Preview") frame = webrtc_ctx.video_transformer.frame result, process_this_frame, face_locations, faces, face_names, score = demo.process_frame(frame, process_this_frame, face_locations, faces, face_names, score) st.video(result) # frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) # FRAME_WINDOW.image(frame) # if ret is not None: # ret, buffer = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY),30]) # x_as_bytes = pickle.dumps(buffer) # s.sendto((x_as_bytes),(server_ip, server_port)) # camera.release() # if ret: # # ret, buffer = cv2.imencode(".jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY)]) # # result, process_this_frame, face_locations, faces, face_names, score = demo.process_frame(frame, process_this_frame, face_locations, faces, face_names, score) # # Display the resulting image # FRAME_WINDOW.image(frame) # else: # print("there is no frame detected") # continue # print(score) # if len(score) > 20: # avg_score = sum(score) / len(score) # st.write(avg_score) # # st.write(f'{demo.convert_distance_to_percentage(avg_score, 0.45)}') # # camera.release() # run = not run # st.session_state['data']['avg_score'] = str(avg_score) ## unrelated if st.button("Confirm"): st.experimental_set_query_params( verified=True, ) with st.spinner('Sending data...'): print(st.session_state['data']) sbt.split_data(st.session_state['data']) st.success('Done!') if __name__ == '__main__': main()