app.py

import gradio as gr
import cv2
from detectron2.engine import DefaultPredictor
from detectron2.config import get_cfg
from detectron2 import model_zoo
from detectron2.utils.visualizer import Visualizer
from detectron2.data import MetadataCatalog

# Setup Detectron2
cfg = get_cfg()
cfg.merge_from_file(model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml"))
cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = 0.5
cfg.MODEL.WEIGHTS = model_zoo.get_checkpoint_url("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")
predictor = DefaultPredictor(cfg)

def detect_objects(image):
    image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    outputs = predictor(image_rgb)
    v = Visualizer(image_rgb, MetadataCatalog.get(cfg.DATASETS.TRAIN[0]), scale=1.0)
    out = v.draw_instance_predictions(outputs["instances"].to("cpu"))
    return out.get_image()

demo = gr.Interface(fn=detect_objects, 
                    inputs=gr.Image(type="numpy"), 
                    outputs="image",
                    title="Detectron2 Object Detection")

demo.launch()