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app.py

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+import streamlit as st
+from main import save_image
+from ultralytics import YOLO
+import shutil
+
+model = YOLO('yolov8m.pt')
+
+st.title('Object Detection')
+
+save_image()
+
+if st.button("Detect Object"):
+    model.predict(source = 'processed_image.jpg', save = True, conf = 0.7)
+    st.image('runs/detect/predict/processed_image.jpg')
+    shutil.rmtree('runs')

main.py

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+import streamlit as st
+from PIL import Image
+import cv2
+import numpy as np
+
+def save_image():
+
+    # st.title("Image Processing and Saving Example")
+
+    # Upload an image using Streamlit's file uploader
+
+    genre = st.radio(
+        "How You Want To Upload Your Image",
+        ('Browse Photos', 'Camera'))
+
+    if genre == 'Camera':
+        uploaded_image = st.camera_input("Take a picture")
+    else:
+        uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+    # uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
+
+    if uploaded_image is not None:
+        # Display the uploaded image
+        # st.image(uploaded_image, caption="Uploaded Image", use_column_width=True)
+
+        # Convert the image to a format compatible with PIL and OpenCV
+        pil_image = Image.open(uploaded_image)
+        opencv_image = np.array(pil_image)
+        opencv_image = cv2.cvtColor(opencv_image, cv2.COLOR_BGR2RGB)
+
+        # Image processing code (You can add any processing you want here)
+
+        # Save the processed image using PIL
+        # st.write("Processed Image")
+        # st.image(pil_image, caption="Processed Image", use_column_width=True)
+
+        # Save the processed image using OpenCV
+        # save_button = st.button("Save Processed Image")
+        # if save_button:
+            # Provide a file path to save the image
+        save_path = "processed_image.jpg"  # You can change the file format or filename here
+        cv2.imwrite(save_path, opencv_image)
+        st.success(f"Image saved as {save_path}")
+
+# if __name__ == "__main__":
+#     main()