Update app.py

app.py

@@ -1,94 +1,42 @@
 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("Upload a video or choose from the default videos to detect falls.")
+st.write("Select a video to see the pre-processed fall detection results.")
 
 # 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": os.path.join(os.getcwd(), "fall_test_01.mp4"),
-        "Video 2": os.path.join(os.getcwd(), "fall_test_02.mp4"),
-        "Video 3": "video3.mp4",
+        "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"),
+        },
     }
 
+    # User selects which video to view
     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 = os.path.join(os.getcwd(), 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)
-        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, "rb") as video_file:
-                left_column.download_button("Download", video_file, "output.mp4")
-        else:
-            st.error("There was an issue processing the video. Please try again.")
+    # Load the corresponding pre-processed video path
+    output_video_path = default_videos[option]["output"]
+
+# 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
+    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")
+else:
+    st.error("Processed video not found. Please check the paths and try again.")