xingqiang commited on
Commit
8bdb918
·
1 Parent(s): 8138129

Add technical report generation feature

Browse files
Files changed (1) hide show
  1. app.py +55 -8
app.py CHANGED
@@ -4,16 +4,50 @@ from PIL import Image
4
  import numpy as np
5
  import os
6
  from pathlib import Path
 
 
7
 
8
  from model import RadarDetectionModel
9
  from feature_extraction import (calculate_amplitude, classify_amplitude,
10
  calculate_distribution_range, classify_distribution_range,
11
  calculate_attenuation_rate, classify_attenuation_rate,
12
- count_reflections, classify_reflections)
 
13
  from report_generation import generate_report, render_report
14
  from utils import plot_detection
15
  from database import save_report, get_report_history
16
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
17
  # Initialize model with HF token from environment
18
  model = None
19
  try:
@@ -31,15 +65,15 @@ def initialize_model():
31
  return None, f"Error initializing model: {str(e)}"
32
  return model, None
33
 
34
- def process_image(image):
35
  if image is None:
36
- return None, "Please upload an image."
37
 
38
  # Initialize model if needed
39
  global model
40
  model, error = initialize_model()
41
  if error:
42
- return None, error
43
 
44
  try:
45
  # Convert to PIL Image if needed
@@ -78,18 +112,29 @@ def process_image(image):
78
  report = generate_report(detection_result, image, features)
79
  detection_image = plot_detection(image, detection_result)
80
 
 
 
 
 
 
 
 
 
 
 
 
81
  # Save report if database is configured
82
  try:
83
  save_report(report)
84
  except Exception as e:
85
  print(f"Warning: Could not save report: {str(e)}")
86
 
87
- return detection_image, render_report(report)
88
 
89
  except Exception as e:
90
  error_msg = f"Error processing image: {str(e)}"
91
  print(error_msg)
92
- return None, error_msg
93
 
94
  def display_history():
95
  try:
@@ -127,11 +172,13 @@ with gr.Blocks(css=css) as iface:
127
  with gr.Row():
128
  with gr.Column(scale=1):
129
  input_image = gr.Image(type="pil", label="Upload Radar Image")
 
130
  analyze_button = gr.Button("Analyze", variant="primary")
131
 
132
  with gr.Column(scale=2):
133
  output_image = gr.Image(type="pil", label="Detection Result")
134
  output_report = gr.HTML(label="Analysis Report")
 
135
 
136
  with gr.Row():
137
  history_button = gr.Button("View History")
@@ -140,8 +187,8 @@ with gr.Blocks(css=css) as iface:
140
  # Set up event handlers
141
  analyze_button.click(
142
  fn=process_image,
143
- inputs=[input_image],
144
- outputs=[output_image, output_report]
145
  )
146
 
147
  history_button.click(
 
4
  import numpy as np
5
  import os
6
  from pathlib import Path
7
+ from datetime import datetime
8
+ import tempfile
9
 
10
  from model import RadarDetectionModel
11
  from feature_extraction import (calculate_amplitude, classify_amplitude,
12
  calculate_distribution_range, classify_distribution_range,
13
  calculate_attenuation_rate, classify_attenuation_rate,
14
+ count_reflections, classify_reflections,
15
+ extract_features)
16
  from report_generation import generate_report, render_report
17
  from utils import plot_detection
18
  from database import save_report, get_report_history
19
 
20
+ class TechnicalReportGenerator:
21
+ def __init__(self):
22
+ self.timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
23
+
24
+ def _generate_technical_section(self, detection_result, features):
25
+ """Generate technical analysis section of the report."""
26
+ tech_doc = "## Technical Analysis\n\n"
27
+
28
+ # Detection Results
29
+ tech_doc += "### Detection Results\n\n```python\n"
30
+ tech_doc += f"Confidence Scores: {detection_result['scores'].tolist()}\n"
31
+ tech_doc += f"Bounding Boxes: {detection_result['boxes'].tolist()}\n"
32
+ tech_doc += f"Labels: {detection_result['labels'].tolist()}\n"
33
+ tech_doc += "```\n\n"
34
+
35
+ # Feature Analysis
36
+ tech_doc += "### Feature Analysis\n\n"
37
+ for feature_name, value in features.items():
38
+ tech_doc += f"- **{feature_name}**: {value}\n"
39
+
40
+ # Signal Processing Details
41
+ tech_doc += "\n### Signal Processing Metrics\n\n"
42
+ tech_doc += "| Metric | Value | Classification |\n"
43
+ tech_doc += "|--------|--------|----------------|\n"
44
+ tech_doc += f"|Amplitude|{features['Amplitude']}|{classify_amplitude(features['Amplitude'])}|\n"
45
+ tech_doc += f"|Distribution Range|{features['Distribution Range']}|{features['Distribution Range']}|\n"
46
+ tech_doc += f"|Attenuation Rate|{features['Attenuation Rate']}|{features['Attenuation Rate']}|\n"
47
+ tech_doc += f"|Reflection Count|{features['Reflection Count']}|{features['Reflection Count']}|\n"
48
+
49
+ return tech_doc
50
+
51
  # Initialize model with HF token from environment
52
  model = None
53
  try:
 
65
  return None, f"Error initializing model: {str(e)}"
66
  return model, None
67
 
68
+ def process_image(image, generate_tech_report=False):
69
  if image is None:
70
+ return None, "Please upload an image.", None
71
 
72
  # Initialize model if needed
73
  global model
74
  model, error = initialize_model()
75
  if error:
76
+ return None, error, None
77
 
78
  try:
79
  # Convert to PIL Image if needed
 
112
  report = generate_report(detection_result, image, features)
113
  detection_image = plot_detection(image, detection_result)
114
 
115
+ # Generate technical report if requested
116
+ tech_report = None
117
+ if generate_tech_report:
118
+ report_gen = TechnicalReportGenerator()
119
+ tech_report = report_gen._generate_technical_section(detection_result, features)
120
+
121
+ # Save technical report to a temporary file
122
+ with tempfile.NamedTemporaryFile(mode='w', delete=False, suffix='.md') as f:
123
+ f.write(tech_report)
124
+ tech_report = f.name
125
+
126
  # Save report if database is configured
127
  try:
128
  save_report(report)
129
  except Exception as e:
130
  print(f"Warning: Could not save report: {str(e)}")
131
 
132
+ return detection_image, render_report(report), tech_report
133
 
134
  except Exception as e:
135
  error_msg = f"Error processing image: {str(e)}"
136
  print(error_msg)
137
+ return None, error_msg, None
138
 
139
  def display_history():
140
  try:
 
172
  with gr.Row():
173
  with gr.Column(scale=1):
174
  input_image = gr.Image(type="pil", label="Upload Radar Image")
175
+ tech_report_checkbox = gr.Checkbox(label="Generate Technical Report", value=False)
176
  analyze_button = gr.Button("Analyze", variant="primary")
177
 
178
  with gr.Column(scale=2):
179
  output_image = gr.Image(type="pil", label="Detection Result")
180
  output_report = gr.HTML(label="Analysis Report")
181
+ tech_report_output = gr.File(label="Technical Report")
182
 
183
  with gr.Row():
184
  history_button = gr.Button("View History")
 
187
  # Set up event handlers
188
  analyze_button.click(
189
  fn=process_image,
190
+ inputs=[input_image, tech_report_checkbox],
191
+ outputs=[output_image, output_report, tech_report_output]
192
  )
193
 
194
  history_button.click(