Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -140,8 +140,8 @@ mask_adapter = None
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@torch.no_grad()
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@torch.autocast(device_type="cuda", dtype=torch.float32)
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def inference_box(input_img, img_state,class_names_input):
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if len(img_state.selected_bboxes) != 2:
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-
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mp.set_start_method("spawn", force=True)
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box_points = img_state.selected_bboxes
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@@ -239,6 +239,12 @@ def get_bbox_with_draw(image, img_state, evt: gr.SelectData):
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)
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return img_state, image
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def initialize_models(sam_path, adapter_pth, model_cfg, cfg):
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cfg = setup_cfg(cfg)
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global sam2_model, clip_model, mask_adapter
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@@ -356,7 +362,7 @@ with gr.Blocks() as demo:
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[input_image, img_state_bbox],
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outputs=[img_state_bbox, input_image]
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).then(
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-
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inputs=[input_image, img_state_bbox,class_names_input_box],
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outputs=[output_image_box]
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)
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@torch.no_grad()
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@torch.autocast(device_type="cuda", dtype=torch.float32)
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def inference_box(input_img, img_state,class_names_input):
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# if len(img_state.selected_bboxes) != 2:
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# return None
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mp.set_start_method("spawn", force=True)
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box_points = img_state.selected_bboxes
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)
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return img_state, image
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+
def check_and_infer_box(img_state_bbox, input_image, class_names_input_box):
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if len(img_state_bbox.selected_bboxes) == 2:
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return inference_box(input_image, img_state_bbox, class_names_input_box)
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return None
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def initialize_models(sam_path, adapter_pth, model_cfg, cfg):
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cfg = setup_cfg(cfg)
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global sam2_model, clip_model, mask_adapter
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[input_image, img_state_bbox],
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outputs=[img_state_bbox, input_image]
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).then(
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check_and_infer_box,
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inputs=[input_image, img_state_bbox,class_names_input_box],
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outputs=[output_image_box]
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)
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