Create app.py

app.py

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+import streamlit as st
+import os
+import cv2
+import numpy as np
+from ultralytics import YOLO
+
+# Load YOLO model
+model = YOLO('yolov8n.pt')  # Ensure you have the correct model file
+
+def process_video(video_path):
+    cap = cv2.VideoCapture(video_path)
+    width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
+    height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
+    fps = int(cap.get(cv2.CAP_PROP_FPS))
+
+    # Create a video writer to save the output
+    output_path = "output.mp4"
+    fourcc = cv2.VideoWriter_fourcc(*"mp4v")
+    out = cv2.VideoWriter(output_path, fourcc, fps, (width, height))
+
+    while cap.isOpened():
+        ret, frame = cap.read()
+        if not ret:
+            break
+
+        results = model(frame)
+        for result in results:
+            for bbox in result.boxes:
+                x1, y1, x2, y2 = map(int, bbox.xyxy[0])
+                confidence = float(bbox.conf)
+                cls = int(bbox.cls)
+
+                if cls == 0:  # Assuming class 0 is 'person'
+                    w = x2 - x1
+                    h = y2 - y1
+
+                    if h < w:
+                        color = (0, 0, 255)  # Red color for fall detected
+                        label = "Fall Detected"
+                    else:
+                        color = (0, 255, 0)  # Green color for normal detection
+                        label = "Person"
+
+                    cv2.rectangle(frame, (x1, y1), (x2, y2), color, 2)
+                    cv2.putText(frame, label, (x1, y1 - 10), cv2.FONT_HERSHEY_SIMPLEX, 0.5, color, 2)
+
+        out.write(frame)
+
+        # Display the frame in Streamlit
+        frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
+        st.image(frame_rgb)
+
+    cap.release()
+    out.release()
+    return output_path
+
+# Streamlit interface
+st.title("Fall Detection App")
+st.write("Upload a video or choose from the default videos to detect falls.")
+
+# Video selection
+default_videos = {
+    "Video 1": os.path.join(os.getcwd(),"fall_test_01.mp4"),
+    "Video 2": "video2.mp4",
+    "Video 3": "video3.mp4",
+}
+
+option = st.selectbox("Choose a video", list(default_videos.keys()))
+uploaded_video = st.file_uploader("Or upload your own video", type=["mp4", "avi", "mov"])
+
+if uploaded_video is not None:
+    video_path = uploaded_video.name
+    with open(video_path, 'wb') as f:
+        f.write(uploaded_video.getbuffer())
+    st.success(f"Uploaded {uploaded_video.name}")
+else:
+    video_path = default_videos[option]
+
+if st.button("Process Video"):
+    output_video = process_video(video_path)
+    st.video(output_video)