first push and pitching idea

.gitignore

+.idea
+
+venv
+Data
\ No newline at end of file

Func/CloseProgram.py

+import cv2
+
+
+def Close(cap):
+    cap.release()
+    cv2.destroyAllWindows()
+    print('closing')
+
+

Func/Helpers.py

+import cv2
+import math
+
+
+def CalculateWidth(size, h, w, imgCropped, imgFixed):
+    c = size / h
+    wCal = math.ceil(c * w)
+    imgResized = cv2.resize(imgCropped, (wCal, size))
+
+    wGap = math.ceil((size - wCal) / 2)
+    imgFixed[:, wGap:wCal + wGap] = imgResized
+
+
+def CalculateHeight(size, h, w, imgCropped, imgFixed):
+    c = size / w
+    hCal = math.ceil(c * h)
+    imgResized = cv2.resize(imgCropped, (size, hCal))
+
+    hGap = math.ceil((size - hCal) / 2)
+    imgFixed[hGap:hCal + hGap, :] = imgResized
+
+
+def GetPrediction(classifier, imgFixed):
+    prediction, index = classifier.getPrediction(imgFixed, draw=False)
+
+    return prediction, index
+
+
+def GetLabels(path):
+    letters = []
+    with open(path, 'r') as file:
+        for line in file:
+            parts = line.strip().split(' ')
+            if len(parts) == 2:
+                letter = parts[1]
+                letters.append(letter)
+
+    return letters

Model/labels.txt

+0 A
+1 B
+2 C
+3 D
+4 E
\ No newline at end of file

SaveData.py

+import time
+
+import cv2
+import numpy as np
+
+from Func.CloseProgram import Close
+from Func.Helpers import CalculateWidth, CalculateHeight
+from cvzone.HandTrackingModule import HandDetector
+
+offset = 20
+size = 300
+folder = "Data/E"
+counter = 0
+
+cap = cv2.VideoCapture(0)
+detector = HandDetector(maxHands=1)
+
+if not cap.isOpened():
+    print("Failed to open video capture.")
+    exit()
+
+while True:
+    success, img = cap.read()
+
+    if not success:
+        print('can\'t read image')
+        break
+
+    hands, img = detector.findHands(img)
+
+    if hands:
+        hand = hands[0]
+        x, y, w, h = hand['bbox']
+
+        imgFixed = np.ones((size, size, 3), np.uint8)
+        imgCropped = img[y - offset:y + h + offset, x - offset:x + w + offset]
+
+        aspectRatio = h / w
+
+        if aspectRatio > 1:
+            CalculateWidth(size, h, w, imgCropped, imgFixed)
+
+        else:
+            CalculateHeight(size, h, w, imgCropped, imgFixed)
+
+        cv2.imshow('ImgCropped', imgCropped)
+        cv2.imshow('ImgFixed', imgFixed)
+
+    cv2.imshow("img", img)
+    key = cv2.waitKey(1)
+
+    if key == ord('p'):
+        Close(cap)
+        break
+
+    if key == ord('s'):
+        counter += 1
+        cv2.imwrite(f'{folder}/Image_{time.time()}.jpg', imgFixed)
+        print(counter)

main.py

+import cv2
+import numpy as np
+from cvzone.HandTrackingModule import HandDetector
+from cvzone.ClassificationModule import Classifier
+
+from Func.CloseProgram import Close
+from Func.Helpers import *
+
+offset = 20
+size = 300
+
+capture = cv2.VideoCapture(0)
+detector = HandDetector(maxHands=1)
+classifier = Classifier("Model/keras_model.h5", "Model/labels.txt")
+letters = GetLabels("Model/labels.txt")
+
+
+if not capture.isOpened():
+    print("Failed to open video capture.")
+    exit()
+
+while True:
+    success, img = capture.read()
+    imgOutput = img.copy()
+
+    if not success:
+        print('can\'t read image')
+        break
+
+    hands, img = detector.findHands(img)
+
+    if hands:
+        hand = hands[0]
+        x, y, w, h = hand['bbox']
+
+        imgFixed = np.ones((size, size, 3), np.uint8)
+        imgCropped = img[y - offset:y + h + offset, x - offset:x + w + offset]
+
+        aspectRatio = h / w
+
+        if aspectRatio > 1:
+            CalculateWidth(size, h, w, imgCropped, imgFixed)
+            prediction, index = GetPrediction(classifier, imgFixed)
+
+        else:
+            CalculateHeight(size, h, w, imgCropped, imgFixed)
+            prediction, index = GetPrediction(classifier, imgFixed)
+
+        print(prediction)
+
+        cv2.putText(imgOutput, letters[index], (x, y), cv2.FONT_HERSHEY_TRIPLEX, 2, (255, 0, 255), 2)
+
+    cv2.imshow("img", imgOutput)
+    key = cv2.waitKey(1)
+
+    if key == ord('p'):
+        Close(capture)
+        break