Upload app.py

app.py

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+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_s_t2i_bn_2e-4_100e_4x8gpus_obj365v1_goldg_train_lvis_minival.py')
+    parser.add_argument('--checkpoint', default='yolo_world_s_clip_base_dual_vlpan_2e-3adamw_32xb16_100e_o365_goldg_train_pretrained-18bea4d2.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)