app.py

import gradio as gr 
import mim 
from mmcv.transforms import Compose
from mmengine.utils import track_iter_progress
from mmdet.registry import VISUALIZERS
from mmdet.apis import init_detector, inference_detector


def sepia(input_img):
    sepia_filter = np.array([
        [0.393, 0.769, 0.189], 
        [0.349, 0.686, 0.168], 
        [0.272, 0.534, 0.131]
    ])
    sepia_img = input_img.dot(sepia_filter.T)
    sepia_img /= sepia_img.max()
    return sepia_img

demo = gr.Interface(sepia, gr.Image(shape=(200, 200)), "image")
demo.launch()