from flask import * from PIL import Image import face_recognition import cv2 import numpy as np import csv from datetime import datetime ############################################ ################# from flask_socketio import SocketIO,emit import base64 ################## app = Flask (__name__ ) ################# app.config['SECRET_KEY'] = 'secret!' socket = SocketIO(app,async_mode="eventlet") ####################### ###################### def base64_to_image(base64_string): # Extract the base64 encoded binary data from the input string base64_data = base64_string.split(",")[1] # Decode the base64 data to bytes image_bytes = base64.b64decode(base64_data) # Convert the bytes to numpy array image_array = np.frombuffer(image_bytes, dtype=np.uint8) # Decode the numpy array as an image using OpenCV image = cv2.imdecode(image_array, cv2.IMREAD_COLOR) return image @socket.on("connect") def test_connect(): print("Connected") emit("my response", {"data": "Connected"}) @socket.on("image") def receive_image(image): # Decode the base64-encoded image data image = base64_to_image(image) image = cv2.resize(image, (224, 224), interpolation=cv2.INTER_AREA) # emit("processed_image", image) # Make the image a numpy array and reshape it to the models input shape. image = np.asarray(image, dtype=np.float32).reshape(1, 224, 224, 3) image = (image / 127.5) - 1 # Predicts the model prediction = model.predict(image) index = np.argmax(prediction) class_name = class_names[index] confidence_score = prediction[0][index] emit("result",{"name":str(class_name),"score":str(confidence_score)}) ####################### @app.route ("/") def home(): return render_template("index.html") if __name__ == '__main__': socket.run(app,host="0.0.0.0", port=7860) ########################################################################### # @app.route('/table') # def show_table(): # # Get the current date # current_date = datetime.now().strftime("%Y-%m-%d") # # Read the CSV file to get attendance data # attendance=[] # try: # with open(f"{current_date}.csv", newline="") as csv_file: # csv_reader = csv.reader(csv_file) # attendance = list(csv_reader) # except FileNotFoundError: # pass # # Render the table.html template and pass the attendance data # return render_template('attendance.html', attendance=attendance) # @app.route("/") # def home(): # return render_template('index.html') # if __name__ == "__main__": # socket.run(app,host="0.0.0.0", port=7860)