diff --git a/main.py b/main.py
index 5ecbc56..3901d32 100644
--- a/main.py
+++ b/main.py
@@ -5,9 +5,13 @@ import cv2 as cv
 import tempfile
 import numpy as np
 import tensorflow as tf
+from crop_hand_skeleton import crop_hand
+from cvzone.HandTrackingModule import HandDetector
 
 if __name__ == "__main__":
+	detector = HandDetector(maxHands=1, mode=True, detectionCon=0.7, minTrackCon=0.8)
 	model = tf.keras.models.load_model('model_pred/VGG16_sign_char_detection_model')
+	
 	st.set_page_config(
 		page_title="Projekt widzenie"
 	)
@@ -22,13 +26,15 @@ if __name__ == "__main__":
 		tfile = tempfile.NamedTemporaryFile(delete=False)
 		tfile.write(upload_movie.read())
 		video_cap = cv.VideoCapture(tfile.name)
-		result, num = segment_video(video_cap, fps=1.5)
+		result, num = segment_video(video_cap, fps=10)
 		st.write(f"Załadowano {num} klatek")
 		for img in result:
-			img2= cv.resize(img,dsize=(224,224))
+			img_skeleton = crop_hand(img, detector)
+			img2= cv.resize(img_skeleton,dsize=(224,224))
+			#breakpoint()
 			img_np = np.asarray(img2)
 			classification = classify(img_np[:,:,::-1], model)
-			st.image(img[:,:,::-1])
+			st.image(img_skeleton[:,:,::-1])
 			st.write(classification)
 			
 			
diff --git a/process_video.py b/process_video.py
index 081dfb6..4e01ebe 100644
--- a/process_video.py
+++ b/process_video.py
@@ -1,7 +1,7 @@
 import cv2
 import tensorflow as tf
 import numpy as np
-from crop_hands_skeleton import crop_hands
+from crop_hand_skeleton import crop_hand
 from cvzone.HandTrackingModule import HandDetector
 
 class_names = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 'U', 'V', 'W', 'X', 'Y', 'Z', 'del', 'nothing', 'space']
@@ -34,7 +34,7 @@ def save_frames(frames, dir):
     detector = HandDetector(maxHands=1, mode=True, detectionCon=0.7, minTrackCon=0.8)
     for i, frame in enumerate(frames):
         print(i)        
-        cv2.imwrite(f"{dir}/frame{i}.jpg", crop_hands(frame, detector))
+        cv2.imwrite(f"{dir}/frame{i}.jpg", crop_hand(frame, detector))
 
 
 def classify(img, model):