Upload app.py

app.py

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+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()