Spaces:
Running
Running
File size: 8,741 Bytes
f83d6df |
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 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 |
#!/usr/bin/env python3
"""
Quick viewer for collected MapCrunch data
"""
import json
import os
from pathlib import Path
from PIL import Image
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
from collections import Counter
def view_data_summary(data_file='data/golden_labels.json'):
"""Display summary of collected data"""
try:
with open(data_file, 'r') as f:
data = json.load(f)
except FileNotFoundError:
print(f"❌ No data file found at {data_file}")
print("💡 Run data collection first: python main.py --mode data --samples 50")
return
samples = data.get('samples', [])
metadata = data.get('metadata', {})
print(f"📊 MapCrunch Data Collection Summary")
print(f"{'='*50}")
print(f"📅 Collection Date: {metadata.get('collection_date', 'Unknown')}")
print(f"📍 Total Samples: {len(samples)}")
print(f"🏙️ Collection Options: {metadata.get('collection_options', {})}")
# Statistics
stats = metadata.get('statistics', {})
if stats:
print(f"\n📈 Statistics:")
for key, value in stats.items():
print(f" {key}: {value}")
# Country distribution
countries = []
for sample in samples:
address = sample.get('address', '')
if address and address != 'Unknown':
# Extract country (usually last part after comma)
country = address.split(', ')[-1].strip()
countries.append(country)
if countries:
country_counts = Counter(countries)
print(f"\n🌍 Top Countries:")
for country, count in country_counts.most_common(10):
print(f" {country}: {count} samples")
# Coordinate coverage
coords_available = sum(1 for s in samples if s.get('lat') is not None)
print(f"\n📍 Coordinate Coverage: {coords_available}/{len(samples)} ({coords_available/len(samples)*100:.1f}%)")
# Thumbnail coverage
thumbnails_available = sum(1 for s in samples if s.get('has_thumbnail'))
print(f"📸 Thumbnail Coverage: {thumbnails_available}/{len(samples)} ({thumbnails_available/len(samples)*100:.1f}%)")
# Sample locations
print(f"\n📍 Sample Locations:")
for i, sample in enumerate(samples[:10]):
address = sample.get('address', 'Unknown')
lat = sample.get('lat', 'N/A')
lng = sample.get('lng', 'N/A')
has_thumb = "📸" if sample.get('has_thumbnail') else "❌"
print(f" {i+1}. {has_thumb} {address} ({lat}, {lng})")
if len(samples) > 10:
print(f" ... and {len(samples) - 10} more")
def create_thumbnail_gallery(data_file='data/golden_labels.json', output_file='data/gallery.html', max_images=100):
"""Create an HTML gallery of collected thumbnails"""
with open(data_file, 'r') as f:
data = json.load(f)
samples = data.get('samples', [])
html = """
<html>
<head>
<title>MapCrunch Collection Gallery</title>
<style>
body { font-family: Arial, sans-serif; background: #f0f0f0; }
h1 { text-align: center; }
.gallery { display: flex; flex-wrap: wrap; justify-content: center; }
.item {
margin: 10px;
background: white;
padding: 10px;
border-radius: 8px;
box-shadow: 0 2px 4px rgba(0,0,0,0.1);
text-align: center;
}
.item img { max-width: 320px; border-radius: 4px; }
.address { font-weight: bold; margin: 5px 0; }
.coords { font-size: 0.9em; color: #666; }
.stats { margin: 20px; text-align: center; }
</style>
</head>
<body>
<h1>MapCrunch Collection Gallery</h1>
"""
# Add statistics
total = len(samples)
with_thumb = sum(1 for s in samples if s.get('has_thumbnail'))
with_coords = sum(1 for s in samples if s.get('lat') is not None)
html += f"""
<div class="stats">
<p>Total Samples: {total} | With Thumbnails: {with_thumb} | With Coordinates: {with_coords}</p>
</div>
<div class="gallery">
"""
# Add thumbnails
count = 0
for sample in samples:
if count >= max_images:
break
if sample.get('thumbnail_path'):
thumb_path = f"thumbnails/{sample['thumbnail_path']}"
address = sample.get('address', 'Unknown')
lat = sample.get('lat', 'N/A')
lng = sample.get('lng', 'N/A')
html += f"""
<div class="item">
<img src="{thumb_path}" alt="{address}">
<div class="address">{address}</div>
<div class="coords">{lat}, {lng}</div>
</div>
"""
count += 1
html += """
</div>
</body>
</html>
"""
with open(output_file, 'w') as f:
f.write(html)
print(f"✅ Gallery created: {output_file}")
print(f"📸 Included {count} images")
print(f"💡 Open in browser: file://{os.path.abspath(output_file)}")
def plot_thumbnails_grid(data_file='data/golden_labels.json', max_images=20):
"""Display a grid of thumbnails using matplotlib"""
with open(data_file, 'r') as f:
data = json.load(f)
samples = [s for s in data['samples'] if s.get('thumbnail_path')][:max_images]
if not samples:
print("❌ No samples with thumbnails found")
return
# Create grid
cols = 5
rows = (len(samples) + cols - 1) // cols
fig, axes = plt.subplots(rows, cols, figsize=(15, rows * 3))
if rows == 1:
axes = axes.reshape(1, -1)
for i, sample in enumerate(samples):
row = i // cols
col = i % cols
thumb_path = f"data/thumbnails/{sample['thumbnail_path']}"
if os.path.exists(thumb_path):
img = mpimg.imread(thumb_path)
axes[row, col].imshow(img)
axes[row, col].set_title(sample.get('address', 'Unknown')[:30] + '...', fontsize=8)
axes[row, col].axis('off')
# Hide empty subplots
for i in range(len(samples), rows * cols):
row = i // cols
col = i % cols
axes[row, col].axis('off')
plt.tight_layout()
plt.suptitle(f'MapCrunch Collection Sample ({len(samples)} locations)', y=1.02)
plt.show()
def export_coordinates_csv(data_file='data/golden_labels.json', output_file='data/coordinates.csv'):
"""Export coordinates to CSV for mapping"""
import csv
with open(data_file, 'r') as f:
data = json.load(f)
samples = data.get('samples', [])
with open(output_file, 'w', newline='', encoding='utf-8') as f:
writer = csv.writer(f)
writer.writerow(['id', 'address', 'latitude', 'longitude', 'has_thumbnail'])
count = 0
for sample in samples:
if sample.get('lat') is not None and sample.get('lng') is not None:
writer.writerow([
sample['id'][:8],
sample.get('address', 'Unknown'),
sample['lat'],
sample['lng'],
'Yes' if sample.get('has_thumbnail') else 'No'
])
count += 1
print(f"✅ Exported {count} coordinates to {output_file}")
def main():
import argparse
parser = argparse.ArgumentParser(description='View collected MapCrunch data')
parser.add_argument('--gallery', action='store_true', help='Create HTML gallery')
parser.add_argument('--grid', action='store_true', help='Show thumbnail grid')
parser.add_argument('--csv', action='store_true', help='Export coordinates to CSV')
parser.add_argument('--data', default='data/golden_labels.json', help='Data file path')
parser.add_argument('--max-images', type=int, default=50, help='Max images for gallery/grid')
args = parser.parse_args()
if not os.path.exists(args.data):
print(f"❌ Data file not found: {args.data}")
print("💡 Run data collection first: python main.py --mode data --samples 50")
return
# Always show summary
view_data_summary(args.data)
# Additional actions
if args.gallery:
print()
create_thumbnail_gallery(args.data, max_images=args.max_images)
if args.grid:
print()
plot_thumbnails_grid(args.data, max_images=args.max_images)
if args.csv:
print()
export_coordinates_csv(args.data)
if __name__ == "__main__":
main() |