chunked/nltk_chunking/tasks_video_classification/chunk_36.txt

mean = image_processor.image_mean
std = image_processor.image_std
if "shortest_edge" in image_processor.size:
     height = width = image_processor.size["shortest_edge"]
else:
     height = image_processor.size["height"]
     width = image_processor.size["width"]
resize_to = (height, width)
num_frames_to_sample = model.config.num_frames
sample_rate = 4
fps = 30
clip_duration = num_frames_to_sample * sample_rate / fps

Now, define the dataset-specific transformations and the datasets respectively.