Update ROIinOpenCV.py

Author: Arshad221b

ROIinOpenCV.py

@@ -9,38 +9,7 @@
 
 
 def prediction(pred):
-    if pred == 0:
-        print('A')
-    elif pred == 1:
-        print('B')
-    
-    elif pred == 2:
-        print('C')
-    
-    elif pred == 3:
-        print('D')
-    
-    elif pred == 14:
-        print('O')
-    
-    elif pred == 8:
-        print('I')
-    
-    elif pred == 20:
-        print('U')
-    
-    elif pred == 21:
-        print('V')
-    
-    elif pred == 22:
-        print('W')
-    
-    elif pred == 24:
-        print('Y')
-    
-    elif pred == 11:
-        print('L')
-        
+    return(chr(pred+ 65))
 
 
 def keras_predict(model, image):
@@ -55,18 +24,18 @@ def keras_process_image(img):
     image_x = 28
     image_y = 28
     img = cv2.resize(img, (1,28,28), interpolation = cv2.INTER_AREA)
-    #img = get_square(img, 28)
-    #img = np.reshape(img, (image_x, image_y))
-    
-    
+  
     return img
 
 
 def crop_image(image, x, y, width, height):
     return image[y:y + height, x:x + width]
 
 def main():
-    while True:  
+    l = []
+    
+    while True:
+        
         cam_capture = cv2.VideoCapture(0)
         _, image_frame = cam_capture.read()  
     # Select ROI
@@ -76,25 +45,26 @@ def main():
         image_grayscale_blurred = cv2.GaussianBlur(image_grayscale, (15,15), 0)
         im3 = cv2.resize(image_grayscale_blurred, (28,28), interpolation = cv2.INTER_AREA)
 
-    
-    
-    #ar = np.array(resized_img)
-    #ar = resized_img.reshape(1,784)
-    
-    
+
 
         im4 = np.resize(im3, (28, 28, 1))
         im5 = np.expand_dims(im4, axis=0)
 
 
         pred_probab, pred_class = keras_predict(model, im5)
-        #print(pred_class, pred_probab)
-        prediction(pred_class)
+    
+        curr = prediction(pred_class)
+        
+        cv2.putText(image_frame, curr, (700, 300), cv2.FONT_HERSHEY_COMPLEX, 4.0, (255, 255, 255), lineType=cv2.LINE_AA)
+            
+            
 
 
     # Display cropped image
-
-        cv2.imshow("Image2",im2)
+        cv2.rectangle(image_frame, (300, 300), (600, 600), (255, 255, 00), 3)
+        cv2.imshow("frame",image_frame)
+        
+        
     #cv2.imshow("Image4",resized_img)
         cv2.imshow("Image3",image_grayscale_blurred)