Merge branch 'main' of github.com:Break-Into-Data/workshop_week1_private

.gitignore

@@ -1,4 +1,5 @@
 .DS_Store
+venv/
 __pycache__/
 datasets/
 runs/

ball_app.py

@@ -0,0 +1,110 @@
+import os
+import time
+import tempfile
+import cv2
+import streamlit as st
+
+from ultralytics import YOLO
+
+
+@st.cache_resource
+def load_model():
+    return YOLO("models/soccer_ball.pt")
+
+
+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))
+    total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+    
+    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
+    fourcc = cv2.VideoWriter_fourcc(*'avc1')
+    out = cv2.VideoWriter(temp_file.name, fourcc, fps, (width, height))
+    
+    progress_text = "Processing video... Please wait."
+    progress_bar = st.progress(0)
+    status_text = st.empty()
+    time_text = st.empty()
+
+    start_time = time.time()
+    
+    for frame_num in range(total_frames):
+        ret, frame = cap.read()
+        if not ret:
+            break
+        
+        results = model(frame)
+        annotated_frame = results[0].plot()
+        out.write(annotated_frame)
+        
+        # Update progress
+        progress = (frame_num + 1) / total_frames
+        elapsed_time = time.time() - start_time
+        estimated_total_time = elapsed_time / progress
+        remaining_time = estimated_total_time - elapsed_time
+
+        progress_bar.progress(progress)
+        status_text.text(f"Processing frame {frame_num+1}/{total_frames}")
+        time_text.text(f"Elapsed time: {elapsed_time:.2f}s | Estimated time remaining: {remaining_time:.2f}s")
+
+    
+    cap.release()
+    out.release()
+    progress_bar.empty()
+    status_text.text(f"Processed {total_frames} frames")
+    time_text.text(f"Total time: {time.time() - start_time:.2f}s")
+    return temp_file.name
+
+
+model = load_model()
+st.title("Soccer Ball Detection App")
+
+# Sidebar for options
+st.sidebar.header("Options")
+video_option = st.sidebar.radio("Choose video source:", ("Use preset video", "Upload video"))
+
+if video_option == "Upload video":
+    uploaded_file = st.sidebar.file_uploader("Choose a video file", type=["mp4", "avi", "mov"])
+    if uploaded_file is not None:
+        tfile = tempfile.NamedTemporaryFile(delete=False, suffix=".mp4")
+        tfile.write(uploaded_file.read())
+        video_path = tfile.name
+else:
+    preset_videos = {
+        "Ronaldo": "preset_videos/Ronaldo.mp4",
+        "Sancho": "preset_videos/CityUtdR video.mp4",
+        "Messi": "preset_videos/Messi.mp4",
+    }
+    selected_video = st.sidebar.selectbox("Select a preset video", list(preset_videos.keys()))
+    video_path = preset_videos[selected_video]
+
+if 'video_path' in locals():
+    st.header("Original Video")
+    st.video(video_path)
+    
+    if st.button("Detect"):
+        with st.spinner("Processing video..."):
+            processed_video_path = process_video(video_path)
+        
+        st.success("Video processing complete!")
+        st.header("Processed Video")
+        st.video(processed_video_path)
+        
+        # Add download link
+        with open(processed_video_path, "rb") as file:
+            btn = st.download_button(
+                label="Download Video",
+                data=file,
+                file_name="processed_video.mp4",
+                mime="video/mp4"
+            )
+        
+        # Clean up temporary files
+        os.unlink(processed_video_path)
+        if video_option == "Upload video":
+            os.unlink(video_path)
+
+st.sidebar.markdown("---")
+st.sidebar.write("Developed with ❤️ by Break Into Data")

requirements.txt

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+ultralytics
+opencv-python
+numpy
+streamlit