Update app.py

app.py

@@ -1,42 +1,89 @@
 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 = os.path.join(os.getcwd(), "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)
+
+    cap.release()
+    out.release()
+
+    # Double-check that the file was saved
+    if os.path.exists(output_path):
+        st.success(f"Video successfully processed and saved to {output_path}")
+    else:
+        st.error("Failed to save the processed video.")
+    
+    return output_path
 
 # Streamlit interface
 st.title("Fall Detection App")
-st.write("Select a video to see the pre-processed fall detection results.")
+st.write("The default video is automatically processed to detect falls.")
 
 # Create two columns
 left_column, right_column = st.columns(2)
 
 # Right column for video selection
 with right_column:
-    # Define the paths for default videos and their corresponding pre-processed outputs
     default_videos = {
-        "Video 1": {
-            "input": os.path.join(os.getcwd(), "fall_test_01.mp4"),
-            "output": os.path.join(os.getcwd(), "processed_fall_test_01.mp4"),
-        },
-        "Video 2": {
-            "input": os.path.join(os.getcwd(), "fall_test_02.mp4"),
-            "output": os.path.join(os.getcwd(), "video_02_results.mp4"),
-        },
-        "Video 3": {
-            "input": os.path.join(os.getcwd(), "fall_test_03.mp4"),
-            "output": os.path.join(os.getcwd(), "processed_fall_test_03.mp4"),
-        },
+        "Video 1": os.path.join(os.getcwd(), "fall_test_01.mp4"),
+        "Video 2": os.path.join(os.getcwd(), "fall_test_02.mp4"),
+        "Video 3": "video3.mp4",
     }
 
-    # User selects which video to view
-    option = st.selectbox("Choose a video", list(default_videos.keys()))
+    # Select the first video as the default input
+    default_video_path = default_videos["Video 1"]
 
-    # Load the corresponding pre-processed video path
-    output_video_path = default_videos[option]["output"]
+    # Display the selection to the user
+    st.write("Default video selected: Video 1")
 
-# Left column to display the pre-processed video
-if os.path.exists(output_video_path):
-    left_column.video(output_video_path)  # Display the pre-processed video
+# Process the default video automatically
+output_video = process_video(default_video_path)
+if output_video and os.path.exists(output_video):
+    left_column.video(output_video)  # Display video in the left column
     left_column.write("Download the processed video:")
-    with open(output_video_path, "rb") as video_file:
-        left_column.download_button("Download", video_file, f"{option}_output.mp4")
+    with open(output_video, "rb") as video_file:
+        left_column.download_button("Download", video_file, "output.mp4")
 else:
-    st.error("Processed video not found. Please check the paths and try again.")
+    st.error("There was an issue processing the video. Please try again.")