app.py

import gradio as gr
import torch
from transformers import VideoMAEForVideoClassification, VideoMAEFeatureExtractor
from PIL import Image
import numpy as np

# Load model & processor
model_name = "OPear/videomae-large-finetuned-UCF-Crime"
model = VideoMAEForVideoClassification.from_pretrained(model_name)
processor = VideoMAEFeatureExtractor.from_pretrained(model_name)

def classify_video(video):
    # video is a numpy array of shape (frames, H, W, C)
    inputs = processor(video, return_tensors="pt")
    with torch.no_grad():
        outputs = model(**inputs)
    logits = outputs.logits
    predicted_class_idx = logits.argmax(-1).item()
    return model.config.id2label[predicted_class_idx]

iface = gr.Interface(fn=classify_video,
                     inputs=gr.Video(),
                     outputs="text",
                     title="Video Classifier using VideoMAE")

iface.launch()