Update app.py

app.py

@@ -7,8 +7,18 @@ from tensorflow.keras.models import Sequential
 from tensorflow.keras.optimizers import legacy
 from tensorflow.keras.layers import Conv3D, LSTM, Dense, Dropout, Bidirectional, MaxPool3D, Activation, Reshape, SpatialDropout3D, BatchNormalization, TimeDistributed, Flatten
 from tensorflow.keras.callbacks import ModelCheckpoint, LearningRateScheduler
+from moviepy.editor import VideoFileClip
 
 
+
+def convert_mp4_to_mpg(input_file):
+    if not os.path.exists(input_file):
+        raise FileNotFoundError(f"Input file '{input_file}' not found.")
+
+    video_clip = VideoFileClip(input_file)
+    video_clip.write_videofile("output.mpg", codec='mpeg2video')
+    video_clip.close()
+
 def load_video(video_path):
 
     cap = cv2.VideoCapture(video_path)
@@ -74,7 +84,8 @@ model.compile(optimizer=optimizer, loss='categorical_crossentropy', metrics=['ac
 model.load_weights('model/checkpoint')
 
 def Predict(Video):
-  sample = load_data(tf.convert_to_tensor(Video))
+  convert_mp4_to_mpg(Video)
+  sample = load_data(tf.convert_to_tensor("output.mpg"))
   yhat = model.predict(tf.expand_dims(sample, axis=0))
   decoded = tf.keras.backend.ctc_decode(yhat, input_length=[75], greedy=True)[0][0].numpy()
   result=[tf.strings.reduce_join([num_to_char(word) for word in sentence]) for sentence in decoded]