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import cv2
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from cvzone.HandTrackingModule import HandDetector
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from cvzone.ClassificationModule import Classifier
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import numpy as np
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import math
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import pyttsx3
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from collections import deque
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engine = pyttsx3.init()
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voices = engine.getProperty('voices')
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engine.setProperty('voice', voices[1].id)
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rate = engine.getProperty('rate')
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engine.setProperty('rate', 125)
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cap = cv2.VideoCapture(0)
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detector = HandDetector(maxHands=1)
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classifier = Classifier("Model/keras_model.h5", "Model/labels.txt")
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offset = 20
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imgSize = 300
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labels = ["A", "B", "C"]
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prediction_history = deque(maxlen=3)
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last_prediction = None
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while True:
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try:
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success, img = cap.read()
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if not success:
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print("Failed to capture image")
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continue
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imgOutput = img.copy()
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hands, img = detector.findHands(img)
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if hands:
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hand = hands[0]
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x, y, w, h = hand['bbox']
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imgWhite = np.ones((imgSize, imgSize, 3), np.uint8) * 255
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try:
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imgCrop = img[y - offset:y + h + offset, x - offset:x + w + offset]
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if imgCrop.size == 0:
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raise ValueError("Empty image crop detected")
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imgCropShape = imgCrop.shape
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aspectRatio = h / w
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if aspectRatio > 1:
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k = imgSize / h
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wCal = math.ceil(k * w)
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imgResize = cv2.resize(imgCrop, (wCal, imgSize))
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imgResizeShape = imgResize.shape
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wGap = math.ceil((imgSize - wCal) / 2)
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imgWhite[:, wGap:wCal + wGap] = imgResize
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else:
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k = imgSize / w
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hCal = math.ceil(k * h)
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imgResize = cv2.resize(imgCrop, (imgSize, hCal))
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imgResizeShape = imgResize.shape
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hGap = math.ceil((imgSize - hCal) / 2)
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imgWhite[hGap:hCal + hGap, :] = imgResize
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try:
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prediction, index = classifier.getPrediction(imgWhite, draw=False)
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print(prediction, index)
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prediction_history.append(labels[index])
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if len(prediction_history) == 3 and len(set(prediction_history)) == 1 and prediction_history[1]!=last_prediction:
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last_prediction=labels[index]
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engine.say(labels[index])
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engine.runAndWait()
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prediction_history = deque(maxlen=3)
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except Exception as e:
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print("Error in classifier prediction:", e)
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except cv2.error as e:
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print("OpenCV error:", e)
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except ValueError as e:
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print(e)
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cv2.rectangle(imgOutput, (x - offset, y - offset - 50),
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(x - offset + 90, y - offset - 50 + 50), (255, 0, 255), cv2.FILLED)
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cv2.putText(imgOutput, labels[index], (x, y - 26), cv2.FONT_HERSHEY_COMPLEX, 1.7, (255, 255, 255), 2)
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cv2.rectangle(imgOutput, (x - offset, y - offset),
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(x + w + offset, y + h + offset), (255, 0, 255), 4)
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cv2.imshow("ImageCrop", imgCrop)
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cv2.imshow("ImageWhite", imgWhite)
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cv2.imshow("Image", imgOutput)
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cv2.waitKey(1)
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except Exception as e:
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print("Unexpected error:", e)
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