Upload 2 files

350epochs.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:d74957f928358205257cad2d295ef9bbee66a4db9678765e9db5a3a567927ca2
+size 22518553

yolostreamlit.py

@@ -0,0 +1,59 @@
+import cv2
+import streamlit as st
+from PIL import Image
+from ultralytics import YOLO
+import tempfile
+import os
+import time
+
+def main():
+    st.title("Gun Detection")
+
+    video_source_option = st.radio("Select Video Source:", ("Video File", "RTSP Stream", "Webcam"))
+
+    if video_source_option == "Video File":
+        video_file = st.file_uploader("Upload Video", type=["mp4", "avi"])
+        if video_file is not None:
+            # Create a temporary file to store the uploaded video
+            with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+                temp_file.write(video_file.read())
+                temp_file_path = temp_file.name
+            detect_objects(temp_file_path)
+            # Remove the temporary file after processing
+            os.unlink(temp_file_path)
+
+    elif video_source_option == "RTSP Stream":
+        rtsp_link = st.text_input("Enter RTSP Link:")
+        if st.button("Start Detection"):
+            detect_objects(rtsp_link)
+
+    elif video_source_option == "Webcam":
+        detect_objects(0)
+
+def detect_objects(video_source):
+    yolo_model = YOLO('300epochs.pt')
+    cap = cv2.VideoCapture(video_source)
+    placeholder = st.empty()
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        # Get predictions
+        results = yolo_model(frame)
+
+        # Draw bounding boxes and labels on the frame
+        annotated_frame = results[0].plot()
+
+        # Convert the annotated frame to RGB (Streamlit uses RGB)
+        annotated_frame_rgb = cv2.cvtColor(annotated_frame, cv2.COLOR_BGR2RGB)
+
+        # Convert the frame to Image
+        img_pil = Image.fromarray(annotated_frame_rgb)
+
+        # Display the frame
+        placeholder.image(img_pil, use_column_width=True)
+        time.sleep(0.1)
+
+if __name__ == '__main__':
+    main()