Update vit_model_test.py

vit_model_test.py

@@ -3,39 +3,26 @@ import torch.nn as nn
 from torch.utils.data import Dataset, DataLoader
 from torchvision import transforms
 from transformers import ViTForImageClassification
-from PIL import Image
 import os
 import pandas as pd
 from sklearn.model_selection import train_test_split
 from sklearn.metrics import accuracy_score, precision_score, confusion_matrix, f1_score, average_precision_score, recall_score
 import matplotlib.pyplot as plt
 import seaborn as sns
-import cv2  # ספריית OpenCV להצגת הוידאו
-from vit_model_traning import labeling, CustomDataset
 
+# פונקציה להצגת סרטון
+def display_video(video_url):
+    video_html = f'''
+    <iframe width="560" height="315" src="{video_url}" frameborder="0" allowfullscreen></iframe>
+    '''
+    # הנח את ה-HTML בדשבורד שלך
+    return video_html
 
 def shuffle_and_split_data(dataframe, test_size=0.2, random_state=59):
     shuffled_df = dataframe.sample(frac=1, random_state=random_state).reset_index(drop=True)
     train_df, val_df = train_test_split(shuffled_df, test_size=test_size, random_state=random_state)
     return train_df, val_df    
 
-
-def play_animation(video_path):
-    cap = cv2.VideoCapture(video_path)
-
-    while cap.isOpened():
-        ret, frame = cap.read()
-        if not ret:
-            break
-        cv2.imshow('Processing Animation', frame)
-
-        # Press 'q' to exit early
-        if cv2.waitKey(25) & 0xFF == ord('q'):
-            break
-
-    cap.release()
-    cv2.destroyAllWindows()
-
 if __name__ == "__main__":
     # Check for GPU availability
     device = torch.device('cuda')
@@ -67,8 +54,12 @@ if __name__ == "__main__":
     true_labels = []
     predicted_labels = []
 
-    # Play animation while processing
-    play_animation('https://huggingface.co/DataScienceProject/Vit/blob/main/0001-0120.mp4')  # מסלול לסרטון האנימציה שלך
+    # קישור לסרטון
+    video_url = 'https://youtube.com/shorts/vGRq060nPYU?feature=share'  # החליפי כאן עם ה-URL של הסרטון שלך
+    video_html = display_video(video_url)
+
+    # הראי את הסרטון לפני החיזוי
+    print(video_html)  # הצג את ה-HTML בדשבורד שלך
 
     with torch.no_grad():
         for images, labels in test_loader:
@@ -100,6 +91,3 @@ if __name__ == "__main__":
     plt.ylabel('True Labels')
     plt.title('Confusion Matrix')
     plt.show()
-
-    # Play animation again if needed
-    # play_animation('path_to_your_animation.mp4')