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# Streamlit Review Dashboard
import streamlit as st
import pandas as pd
import json
import os
from pathlib import Path
from typing import List, Dict
try:
import plotly.express as px
import plotly.graph_objects as go
PLOTLY_AVAILABLE = True
except ImportError:
PLOTLY_AVAILABLE = False
st.warning("Plotly not available. Some visualizations will be disabled.")
def load_events(json_path: str) -> List[Dict]:
"""Load events from JSON file"""
if not os.path.exists(json_path):
return []
with open(json_path, 'r') as f:
data = json.load(f)
return data.get('events', [])
def load_checkpoints(checkpoint_dir: str) -> List[str]:
"""List available checkpoint files"""
if not os.path.exists(checkpoint_dir):
return []
checkpoints = sorted([
f for f in os.listdir(checkpoint_dir)
if f.startswith('checkpoint_') and f.endswith('.json')
])
return checkpoints
def render_event_summary(events: List[Dict]):
"""Render event summary statistics"""
if not events:
st.info("No events loaded")
return
# Count events by type
event_counts = {}
for event in events:
event_type = event.get('type', 'unknown')
event_counts[event_type] = event_counts.get(event_type, 0) + 1
# Display metrics
col1, col2, col3, col4, col5 = st.columns(5)
with col1:
st.metric("Total Events", len(events))
with col2:
st.metric("Passes", event_counts.get('pass', 0))
with col3:
st.metric("Dribbles", event_counts.get('dribble', 0))
with col4:
st.metric("Shots", event_counts.get('shot', 0))
with col5:
st.metric("Recoveries", event_counts.get('recovery', 0))
def render_event_timeline(events: List[Dict]):
"""Render event timeline visualization"""
if not events:
return
if not PLOTLY_AVAILABLE:
st.info("Plotly not available for timeline visualization")
return
# Prepare data
timeline_data = []
for event in events:
timeline_data.append({
'frame': event.get('start_frame', 0),
'type': event.get('type', 'unknown'),
'confidence': event.get('confidence', 0.0)
})
df = pd.DataFrame(timeline_data)
# Create timeline plot
fig = px.scatter(
df,
x='frame',
y='type',
color='confidence',
color_continuous_scale='Viridis',
title='Event Timeline',
labels={'frame': 'Frame Number', 'type': 'Event Type'}
)
st.plotly_chart(fig, use_container_width=True)
def render_event_table(events: List[Dict]):
"""Render events in a table"""
if not events:
return
# Convert to DataFrame
table_data = []
for event in events:
table_data.append({
'ID': event.get('id', ''),
'Type': event.get('type', ''),
'Start Frame': event.get('start_frame', 0),
'End Frame': event.get('end_frame', 0),
'Confidence': f"{event.get('confidence', 0.0):.2f}",
'Players': len(event.get('involved_players', []))
})
df = pd.DataFrame(table_data)
st.dataframe(df, use_container_width=True)
def render_pitch_map(events: List[Dict]):
"""Render events on pitch map"""
if not events:
return
if not PLOTLY_AVAILABLE:
st.info("Plotly not available for pitch map visualization")
return
# Extract locations
pass_locs = []
shot_locs = []
dribble_locs = []
for event in events:
event_type = event.get('type', '')
start_loc = event.get('start_location', {})
end_loc = event.get('end_location', {})
if event_type == 'pass':
pass_locs.append({
'x': [start_loc.get('x', 0), end_loc.get('x', 0)],
'y': [start_loc.get('y', 0), end_loc.get('y', 0)]
})
elif event_type == 'shot':
shot_locs.append({
'x': end_loc.get('x', 0),
'y': end_loc.get('y', 0)
})
elif event_type == 'dribble':
dribble_locs.append({
'x': end_loc.get('x', 0),
'y': end_loc.get('y', 0)
})
# Create pitch visualization
fig = go.Figure()
# Draw pitch outline (105m x 68m)
pitch_x = [-52.5, 52.5, 52.5, -52.5, -52.5]
pitch_y = [-34, -34, 34, 34, -34]
fig.add_trace(go.Scatter(
x=pitch_x,
y=pitch_y,
mode='lines',
name='Pitch',
line=dict(color='green', width=2)
))
# Draw passes
for pass_loc in pass_locs:
fig.add_trace(go.Scatter(
x=pass_loc['x'],
y=pass_loc['y'],
mode='lines+markers',
name='Pass',
line=dict(color='blue', width=1),
marker=dict(size=5)
))
# Draw shots
if shot_locs:
shot_x = [loc['x'] for loc in shot_locs]
shot_y = [loc['y'] for loc in shot_locs]
fig.add_trace(go.Scatter(
x=shot_x,
y=shot_y,
mode='markers',
name='Shot',
marker=dict(size=10, color='red', symbol='star')
))
# Draw dribbles
if dribble_locs:
dribble_x = [loc['x'] for loc in dribble_locs]
dribble_y = [loc['y'] for loc in dribble_locs]
fig.add_trace(go.Scatter(
x=dribble_x,
y=dribble_y,
mode='markers',
name='Dribble',
marker=dict(size=8, color='orange', symbol='circle')
))
fig.update_layout(
title='Event Map on Pitch',
xaxis_title='X (meters)',
yaxis_title='Y (meters)',
showlegend=True,
width=800,
height=600
)
st.plotly_chart(fig, use_container_width=True)
def main():
"""Main Streamlit app"""
st.set_page_config(page_title="Soccer Analysis Dashboard", layout="wide")
st.title("Soccer Analysis Pipeline - Review Dashboard")
# Sidebar for file selection
st.sidebar.header("Data Selection")
output_dir = st.sidebar.text_input("Output Directory", value="data/output")
# Load events
json_path = os.path.join(output_dir, "events.json")
events = load_events(json_path)
# Checkpoint selection
checkpoint_dir = os.path.join(output_dir, "checkpoints")
checkpoints = load_checkpoints(checkpoint_dir)
if checkpoints:
st.sidebar.subheader("Checkpoints")
selected_checkpoint = st.sidebar.selectbox(
"Select Checkpoint",
options=checkpoints,
index=len(checkpoints) - 1 if checkpoints else 0
)
if selected_checkpoint:
checkpoint_path = os.path.join(checkpoint_dir, selected_checkpoint)
checkpoint_events = load_events(checkpoint_path)
if checkpoint_events:
st.sidebar.info(f"Loaded {len(checkpoint_events)} events from checkpoint")
# Main content
if events:
st.header("Event Summary")
render_event_summary(events)
st.header("Event Timeline")
render_event_timeline(events)
st.header("Pitch Map")
render_pitch_map(events)
st.header("Event Details")
render_event_table(events)
else:
st.warning(f"No events found at {json_path}")
st.info("Run the main pipeline to generate events")
if __name__ == "__main__":
main()
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