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app.py
CHANGED
@@ -17,10 +17,10 @@ from isegm.inference.predictors import BasePredictor, get_predictor
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# Global scope objects.
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###################################
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URL_PREFIX = "https://huggingface.co/curt-park/interactive-segmentation/resolve/main"
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-
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POS_COLOR, NEG_COLOR = "#3498DB", "#C70039"
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ERR_X, ERR_Y = 5.5, 1.0
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MODELS = {"RITM": "ritm_coco_lvis_h18_itermask.pth"}
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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clicker = ck.Clicker()
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predictor = None
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@@ -71,7 +71,7 @@ def predict(image: Image, mask: torch.Tensor, threshold: float = 0.5) -> torch.T
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# Sidebar GUI
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###################################
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# Items in the sidebar.
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model = st.sidebar.selectbox("Select a
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threshold = st.sidebar.slider("Threshold: ", 0.0, 1.0, 0.5)
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marking_type = st.sidebar.radio("Click Type:", ("Positive", "Negative"))
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image_path = st.sidebar.file_uploader("Background Image:", type=["png", "jpg", "jpeg"])
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# Global scope objects.
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###################################
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URL_PREFIX = "https://huggingface.co/curt-park/interactive-segmentation/resolve/main"
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MODELS = {"RITM": "ritm_coco_lvis_h18_itermask.pth"}
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POS_COLOR, NEG_COLOR = "#3498DB", "#C70039"
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CANVAS_HEIGHT, CANVAS_WIDTH = 600, 600
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ERR_X, ERR_Y = 5.5, 1.0
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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clicker = ck.Clicker()
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predictor = None
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# Sidebar GUI
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###################################
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# Items in the sidebar.
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model = st.sidebar.selectbox("Select a Method:", tuple(MODELS.keys()))
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threshold = st.sidebar.slider("Threshold: ", 0.0, 1.0, 0.5)
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marking_type = st.sidebar.radio("Click Type:", ("Positive", "Negative"))
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image_path = st.sidebar.file_uploader("Background Image:", type=["png", "jpg", "jpeg"])
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