Update app.py

app.py

@@ -1,69 +1,44 @@
-import os
-os.system("pip uninstall -y mmcv-full")
-os.system("mim install 'mmengine>=0.6.0'")
-# os.system("pip install mmcv==2.0.1 -f https://download.openmmlab.com/mmcv/dist/cu118/torch2.0/index.html")
-os.system("mim install 'mmcv-lite==2.0.1'")
-os.system("mim install 'mmdet>=3.0.0,<4.0.0'")
-os.system("mim install 'mmyolo'")
-os.system("pip install -e .")
-
-import argparse
-import os.path as osp
-
-from mmengine.config import Config, DictAction
-from mmengine.runner import Runner
-from mmengine.dataset import Compose
-from mmyolo.registry import RUNNERS
-
-from tools.demo import demo
-
-
-def parse_args():
-    parser = argparse.ArgumentParser(
-        description='YOLO-World Demo')
-    parser.add_argument('--config', default='configs/pretrain/yolo_world_xl_t2i_bn_2e-4_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py')
-    parser.add_argument('--checkpoint', default='yolo_world_v2_xl_obj365v1_goldg_cc3mlite_pretrain.pth')
-    parser.add_argument(
-        '--work-dir',
-        help='the directory to save the file containing evaluation metrics')
-    parser.add_argument(
-        '--cfg-options',
-        nargs='+',
-        action=DictAction,
-        help='override some settings in the used config, the key-value pair '
-        'in xxx=yyy format will be merged into config file. If the value to '
-        'be overwritten is a list, it should be like key="[a,b]" or key=a,b '
-        'It also allows nested list/tuple values, e.g. key="[(a,b),(c,d)]" '
-        'Note that the quotation marks are necessary and that no white space '
-        'is allowed.')
-    args = parser.parse_args()
-    return args
-
-
-if __name__ == '__main__':
-    args = parse_args()
-
-    # load config
-    cfg = Config.fromfile(args.config)
-    if args.cfg_options is not None:
-        cfg.merge_from_dict(args.cfg_options)
-
-    if args.work_dir is not None:
-        cfg.work_dir = args.work_dir
-    elif cfg.get('work_dir', None) is None:
-        cfg.work_dir = osp.join('./work_dirs',
-                                osp.splitext(osp.basename(args.config))[0])
-
-    cfg.load_from = args.checkpoint
-
-    if 'runner_type' not in cfg:
-        runner = Runner.from_cfg(cfg)
-    else:
-        runner = RUNNERS.build(cfg)
-
-    runner.call_hook('before_run')
-    runner.load_or_resume()
-    pipeline = cfg.test_dataloader.dataset.pipeline
-    runner.pipeline = Compose(pipeline)
-    runner.model.eval()
-    demo(runner, args, cfg)
+import gradio as gr
+import PIL.Image as Image
+
+from ultralytics import ASSETS, YOLO
+
+model = None
+
+
+def predict_image(img, conf_threshold, iou_threshold, model_name):
+    """Predicts objects in an image using a YOLOv8 model with adjustable confidence and IOU thresholds."""
+    model = YOLO(model_name)
+    results = model.predict(
+        source=img,
+        conf=conf_threshold,
+        iou=iou_threshold,
+        show_labels=True,
+        show_conf=True,
+        imgsz=640,
+    )
+
+    for r in results:
+        im_array = r.plot()
+        im = Image.fromarray(im_array[..., ::-1])
+
+    return im
+
+
+iface = gr.Interface(
+    fn=predict_image,
+    inputs=[
+        gr.Image(type="pil", label="Upload Image"),
+        gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
+        gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold"),
+        gr.Radio(choices=["yolo11n", "yolo11s", "yolo11n-seg", "yolo11s-seg", "yolo11n-pose", "yolo11s-pose"], label="Model Name", value="yolo11n"),
+    ],
+    outputs=gr.Image(type="pil", label="Result"),
+    title="Ultralytics Gradio Application 🚀",
+    description="Upload images for inference. The Ultralytics YOLO11n model is used by default.",
+    examples=[
+        [ASSETS / "bus.jpg", 0.25, 0.45, "yolo11n.pt"],
+        [ASSETS / "zidane.jpg", 0.25, 0.45, "yolo11n.pt"],
+    ],
+)
+iface.launch(share=True)