Spaces:
Sleeping
Sleeping
File size: 2,836 Bytes
26784f8 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
import streamlit as st
import cv2
import tempfile
import numpy as np
from collections import defaultdict
# Import your existing functions here
# from quadball_tracker import detect_balls, update_trackers, check_events, get_quadrant, COLOR_RANGES
def process_video(video_path):
cap = cv2.VideoCapture(video_path)
frame_count = 0
ball_trackers = defaultdict(lambda: defaultdict(dict))
events = []
total_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
progress_bar = st.progress(0)
status_text = st.empty()
while cap.isOpened():
ret, frame = cap.read()
if not ret:
break
frame_count += 1
progress_bar.progress(frame_count / total_frames)
status_text.text(f"Processing frame {frame_count}/{total_frames}")
try:
balls = detect_balls(frame)
update_trackers(ball_trackers, balls, frame_count)
new_events = check_events(ball_trackers, frame_count)
events.extend(new_events)
except Exception as e:
st.error(f"Error processing frame {frame_count}: {str(e)}")
cap.release()
return events
st.title('QuadBall Tracker 🔴🟢🔵🟡')
st.write("""
Welcome to QuadBall Tracker! This application uses computer vision to track colored balls
across different quadrants in a video. Upload your video to get started!
""")
uploaded_file = st.file_uploader("Choose a video file", type=["mp4", "avi", "mov"])
if uploaded_file is not None:
tfile = tempfile.NamedTemporaryFile(delete=False)
tfile.write(uploaded_file.read())
st.video(tfile.name)
if st.button('Process Video'):
events = process_video(tfile.name)
st.success('Video processing complete!')
st.subheader('Event Log')
for event in events:
st.write(f"Time: {event['time']}, Quadrant: {event['quadrant']}, "
f"Color: {event['color']}, Type: {event['type']}")
# Create a DataFrame for easy filtering
import pandas as pd
df = pd.DataFrame(events)
st.subheader('Filter Events')
color_filter = st.multiselect('Select colors', df['color'].unique())
quadrant_filter = st.multiselect('Select quadrants', df['quadrant'].unique())
filtered_df = df
if color_filter:
filtered_df = filtered_df[filtered_df['color'].isin(color_filter)]
if quadrant_filter:
filtered_df = filtered_df[filtered_df['quadrant'].isin(quadrant_filter)]
st.dataframe(filtered_df)
st.sidebar.title('About')
st.sidebar.info('This application uses computer vision to track colored balls across video quadrants. '
'Upload a video to see it in action!') |