Spaces:
Build error
Build error
File size: 14,671 Bytes
a57c376 e0a62f3 a57c376 f6092ab a57c376 e0a62f3 a57c376 e0a62f3 a57c376 e0a62f3 a57c376 f6092ab a57c376 e0a62f3 a57c376 f6092ab a57c376 e0a62f3 a57c376 e0a62f3 a57c376 e0a62f3 a57c376 e0a62f3 a57c376 b3265cf e0a62f3 b3265cf e0a62f3 b3265cf e0a62f3 b3265cf e0a62f3 b3265cf e0a62f3 b3265cf e0a62f3 b3265cf a57c376 e0a62f3 a57c376 e0a62f3 a57c376 e0a62f3 a57c376 f38c124 | 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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 | # PHASE 6: User Interface with Gradio
# Add this to your notebook after Phase 5
import gradio as gr
import cv2
import numpy as np
from PIL import Image, ImageDraw, ImageFont
import tempfile
import os
import matplotlib.pyplot as plt
from io import BytesIO
import base64
class CarDamageWebInterface:
def __init__(self, damage_system):
"""Initialize web interface"""
self.damage_system = damage_system
print("Initializing Web Interface...")
def process_uploaded_image(self, image):
"""Process uploaded image and return results"""
if image is None:
return "Please upload an image", None, "No analysis available"
try:
# Save uploaded image temporarily
with tempfile.NamedTemporaryFile(delete=False, suffix='.jpg') as tmp_file:
# Convert numpy array to PIL Image if needed
if isinstance(image, np.ndarray):
pil_image = Image.fromarray(image)
else:
pil_image = image
pil_image.save(tmp_file.name)
temp_path = tmp_file.name
# Run complete analysis
result = self.damage_system.analyze_car_damage(temp_path)
# Clean up temp file
os.unlink(temp_path)
if not result or not result.get('classified_damages'):
return "No significant damage detected in the image.", image, "No repair costs estimated."
# Process results for display
classified_damages = result['classified_damages']
cost_analysis = result.get('cost_analysis', {})
# Create result image with annotations
result_image = self._create_annotated_image(image, classified_damages)
# Create detailed report
report = self._create_detailed_report(classified_damages, cost_analysis)
# Create cost summary
if cost_analysis:
cost_summary = f"Total Estimated Repair Cost: ${cost_analysis['total_cost']:.2f}"
else:
cost_summary = "Cost estimation not available"
return report, result_image, cost_summary
except Exception as e:
error_msg = f"Error processing image: {str(e)}"
print(error_msg)
return error_msg, image, "Analysis failed"
def _create_annotated_image(self, original_image, classified_damages):
"""Create annotated image with damage highlights"""
try:
# Convert to PIL Image if numpy array
if isinstance(original_image, np.ndarray):
img = Image.fromarray(original_image)
else:
img = original_image.copy()
# Create drawing context
draw = ImageDraw.Draw(img)
# Color mapping for different damage types
damage_colors = {
'scratch': (255, 255, 0), # Yellow
'dent': (255, 0, 0), # Red
'crack': (0, 255, 0), # Green
'rust': (255, 165, 0), # Orange
'broken': (128, 0, 128), # Purple
'unknown': (255, 255, 255) # White
}
# Draw bounding boxes and labels for each damage
for i, damage in enumerate(classified_damages):
damage_type = damage.get('type', 'unknown')
severity = damage.get('severity', 'unknown')
confidence = damage.get('confidence', 0)
# Get color for this damage type
color = damage_colors.get(damage_type, damage_colors['unknown'])
# Create bounding box (simulate damage location)
img_width, img_height = img.size
x = (i * 150 + 50) % (img_width - 200)
y = (i * 100 + 50) % (img_height - 150)
# Draw rectangle
draw.rectangle([x, y, x + 150, y + 100], outline=color, width=3)
# Create label text
label = f"{damage_type.upper()}\n{severity}\n{confidence:.1%}"
# Draw label background
draw.rectangle([x, y - 60, x + 150, y], fill=color, outline=color)
# Draw label text
try:
# Try to use default font
draw.text((x + 5, y - 55), label, fill=(0, 0, 0))
except:
# Fallback if font fails
draw.text((x + 5, y - 55), label, fill=(0, 0, 0))
return img
except Exception as e:
print(f"Error creating annotated image: {e}")
return original_image
def _create_detailed_report(self, classified_damages, cost_analysis):
"""Create detailed text report"""
report = "CAR DAMAGE ANALYSIS REPORT\n"
report += "=" * 50 + "\n\n"
# Summary
report += f"SUMMARY:\n"
report += f"β’ Total damages detected: {len(classified_damages)}\n"
# Count damage types
damage_counts = {}
severity_counts = {}
for damage in classified_damages:
dtype = damage.get('type', 'unknown')
severity = damage.get('severity', 'unknown')
damage_counts[dtype] = damage_counts.get(dtype, 0) + 1
severity_counts[severity] = severity_counts.get(severity, 0) + 1
report += f"β’ Damage types found: {', '.join(damage_counts.keys())}\n"
report += f"β’ Severity distribution: {dict(severity_counts)}\n\n"
# Detailed damage list
report += "DETAILED DAMAGE LIST:\n"
report += "-" * 30 + "\n"
for i, damage in enumerate(classified_damages, 1):
report += f"{i}. {damage.get('type', 'Unknown').upper()}\n"
report += f" Severity: {damage.get('severity', 'Unknown')}\n"
report += f" Confidence: {damage.get('confidence', 0):.1%}\n"
report += f" Area: {damage.get('area_percentage', 0):.2f}% of image\n"
if 'estimated_cost' in damage:
report += f" Estimated Cost: ${damage['estimated_cost']:.2f}\n"
report += "\n"
# Cost analysis
if cost_analysis:
report += "COST ANALYSIS:\n"
report += "-" * 20 + "\n"
report += f"Labor Cost: ${cost_analysis.get('labor_cost', 0):.2f}\n"
report += f"Parts Cost: ${cost_analysis.get('parts_cost', 0):.2f}\n"
report += f"Additional Fees: ${cost_analysis.get('additional_cost', 0):.2f}\n"
report += f"TOTAL: ${cost_analysis.get('total_cost', 0):.2f}\n\n"
# Recommendations
report += "π‘ RECOMMENDATIONS:\n"
report += "-" * 20 + "\n"
high_severity = [d for d in classified_damages if d.get('severity') == 'high']
if high_severity:
report += " High severity damages detected - immediate repair recommended\n"
if any(d.get('type') == 'rust' for d in classified_damages):
report += "Rust detected - treat immediately to prevent spreading\n"
if any(d.get('type') == 'crack' for d in classified_damages):
report += "Cracks found - structural integrity may be compromised\n"
if len(classified_damages) > 5:
report += "Multiple damages - consider comprehensive repair package\n"
return report
def create_interface(self):
"""Create and return Gradio interface"""
# Custom CSS for styling
css = """
.gradio-container {
max-width: 1200px !important;
font-family: 'Segoe UI', sans-serif;
}
.main-header {
text-align: center;
color: #2c3e50;
margin-bottom: 30px;
}
.upload-area {
border: 2px dashed #3498db;
border-radius: 10px;
padding: 20px;
}
.result-area {
border: 1px solid #bdc3c7;
border-radius: 8px;
padding: 15px;
margin: 10px 0;
}
"""
with gr.Blocks(css=css, title="Car Damage Detection AI") as interface:
# Header
gr.HTML("""
<div class="main-header">
<h1>Car Damage Detection & Cost Estimation</h1>
<p>Upload a photo of your car to get instant damage analysis and repair cost estimates</p>
</div>
""")
with gr.Row():
# Input Column
with gr.Column(scale=1):
gr.HTML("<h3>Upload Car Image</h3>")
image_input = gr.Image(
label="Car Image",
type="pil",
height=400,
elem_classes="upload-area"
)
analyze_btn = gr.Button(
"Analyze Damage",
variant="primary",
size="lg"
)
# Example images section
gr.HTML("<h4>Instructions:</h4>")
gr.HTML("""
<ul>
<li>Upload a clear photo of your car</li>
<li>Ensure good lighting and visibility</li>
<li>Include the damaged areas in the frame</li>
<li>Supported formats: JPG, PNG, JPEG</li>
</ul>
""")
# Output Column
with gr.Column(scale=2):
gr.HTML("<h3>Analysis Results</h3>")
# Results tabs
with gr.Tabs():
with gr.TabItem("Detailed Report"):
report_output = gr.Textbox(
label="Analysis Report",
lines=20,
max_lines=30,
elem_classes="result-area"
)
with gr.TabItem("Annotated Image"):
image_output = gr.Image(
label="Damage Detection Results",
height=400,
elem_classes="result-area"
)
with gr.TabItem("Cost Summary"):
cost_output = gr.Textbox(
label="Repair Cost Estimate",
lines=5,
elem_classes="result-area"
)
# Connect the analyze button to processing function
analyze_btn.click(
fn=self.process_uploaded_image,
inputs=[image_input],
outputs=[report_output, image_output, cost_output]
)
# Auto-analyze when image is uploaded
image_input.change(
fn=self.process_uploaded_image,
inputs=[image_input],
outputs=[report_output, image_output, cost_output]
)
return interface
# Initialize and launch the web interface
def launch_car_damage_app():
"""Launch the car damage detection web app"""
print("Launching Car Damage Detection Web App...")
# Create damage detection system (assuming it's already created from previous phases)
try:
# Use the damage system created in previous phases
damage_system = complete_car_damage_system # This should exist from Phase 5
# Create web interface
web_interface = CarDamageWebInterface(damage_system)
# Create and launch Gradio interface
app = web_interface.create_interface()
# Launch with public sharing enabled
app.launch(
share=True, # Creates public link
debug=True,
server_name="0.0.0.0",
server_port=7860,
show_error=True
)
except NameError:
print("Error: Complete damage system not found!")
print("Please run Phases 1-5 first to create the damage detection system.")
return None
except Exception as e:
print(f"Error launching app: {e}")
return None
# Alternative: Create a demo interface if damage system is not available
def create_demo_interface():
"""Create a demo interface for testing"""
class DemoCarDamageSystem:
def analyze_car_damage(self, image_path):
"""Demo analysis function"""
import random
# Simulate analysis results
damages = []
damage_types = ['scratch', 'dent', 'crack', 'rust']
severities = ['low', 'medium', 'high']
num_damages = random.randint(1, 4)
for i in range(num_damages):
damage = {
'type': random.choice(damage_types),
'severity': random.choice(severities),
'confidence': random.uniform(0.6, 0.95),
'area_percentage': random.uniform(0.5, 5.0),
'estimated_cost': random.uniform(100, 2000)
}
damages.append(damage)
total_cost = sum(d['estimated_cost'] for d in damages)
return {
'classified_damages': damages,
'cost_analysis': {
'labor_cost': total_cost * 0.6,
'parts_cost': total_cost * 0.3,
'additional_cost': total_cost * 0.1,
'total_cost': total_cost
}
}
# Create demo system and interface
demo_system = DemoCarDamageSystem()
web_interface = CarDamageWebInterface(demo_system)
print("π Launching DEMO version of Car Damage Detection App...")
print("This is a demonstration with simulated results.")
app = web_interface.create_interface()
app.launch(share=True, debug=True)
# Instructions for Phase 6
print("=" * 60)
print("π PHASE 6: WEB INTERFACE SETUP COMPLETE!")
print("=" * 60)
print()
print("β¨ FEATURES INCLUDED:")
print("β’ πΈ Drag & drop image upload")
print("β’ π Real-time damage analysis")
print("β’ π Detailed damage reports")
print("β’ πΌοΈ Annotated result images")
print("β’ π° Cost estimation breakdown")
print("β’ π± Mobile-friendly interface")
print("β’ π Public sharing capability")
print()
print("π― Ready to launch your Car Damage Detection Web App!")
create_demo_interface()
|