Update app.py
Browse files
app.py
CHANGED
@@ -1,7 +1,9 @@
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import glob
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import gradio as gr
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from ultralytics import YOLO
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model_path = "best.pt"
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model = YOLO(model_path)
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@@ -9,22 +11,39 @@ PREDICT_KWARGS = {
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"conf": 0.15,
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}
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title = "OOI RCA Digital Still Camera Benthic Megafauna Detector"
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description = ""
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examples = glob.glob("images/*.png")
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import streamlit as st
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import glob
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from ultralytics import YOLO
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from PIL import Image
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# Load the YOLO model
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model_path = "best.pt"
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model = YOLO(model_path)
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"conf": 0.15,
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}
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# Title and description for the app
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st.title("OOI RCA Digital Still Camera Benthic Megafauna Detector")
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st.write("This app uses a YOLO model to detect benthic megafauna in images.")
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# Load example images
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examples = glob.glob("images/*.png")
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# Display list of example images to choose from
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st.sidebar.title("Example Images")
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selected_example = st.sidebar.selectbox("Select an example image", examples)
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# Display the selected example image
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if selected_example:
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st.image(selected_example, caption="Selected Example Image", use_column_width=True)
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# File uploader for custom images
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uploaded_file = st.file_uploader("Or upload an image", type=["png", "jpg", "jpeg"])
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# Select which image to use for prediction
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if uploaded_file is not None:
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image = Image.open(uploaded_file)
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st.image(image, caption="Uploaded Image", use_column_width=True)
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image_path = uploaded_file
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elif selected_example:
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image = Image.open(selected_example)
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image_path = selected_example
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else:
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image = None
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image_path = None
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# Run the YOLO model on the selected image
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if image_path is not None:
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results = model.predict(image_path, **PREDICT_KWARGS)
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st.image(results[0].plot()[:, :, ::-1], caption="Predicted Image", use_column_width=True)
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else:
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st.write("Please upload an image or select an example to proceed.")
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