app.py

import gradio as gr
import cv2
import numpy as np
import pandas as pd
import pydicom
import io
from PIL import Image
import openpyxl
from openpyxl.utils import get_column_letter, column_index_from_string
import logging
import time
import traceback
from functools import wraps
import sys

print("Starting imports completed...")

# Set up logging
logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('dicom_analyzer_debug.log'),
        logging.StreamHandler(sys.stdout)
    ]
)

logger = logging.getLogger(__name__)

def debug_decorator(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        logger.debug(f"Entering {func.__name__}")
        start_time = time.time()
        try:
            result = func(*args, **kwargs)
            logger.debug(f"Function {func.__name__} completed successfully")
            return result
        except Exception as e:
            logger.error(f"Error in {func.__name__}: {str(e)}")
            logger.error(traceback.format_exc())
            raise
        finally:
            end_time = time.time()
            logger.debug(f"Execution time: {end_time - start_time:.4f} seconds")
    return wrapper

class DicomAnalyzer:
    def __init__(self):
        self.results = []
        self.circle_diameter = 9.0  # Changed to float for precise calculations
        self.zoom_factor = 1.0
        self.current_image = None
        self.dicom_data = None
        self.display_image = None
        self.marks = []  # Store (x, y, diameter) for each mark
        self.original_image = None
        self.original_display = None
        # Pan position
        self.pan_x = 0
        self.pan_y = 0
        self.max_pan_x = 0
        self.max_pan_y = 0
        # Circle color in BGR
        self.CIRCLE_COLOR = (0, 255, 255)  # BGR Yellow
        print("DicomAnalyzer initialized...")

    def load_dicom(self, file):
        try:
            if file is None:
                return None, "No file uploaded"
            
            if hasattr(file, 'name'):
                dicom_data = pydicom.dcmread(file.name)
            else:
                dicom_data = pydicom.dcmread(file)
                
            image = dicom_data.pixel_array.astype(np.float32)
            
            # Store original pixel values before any scaling
            self.original_image = image.copy()
            
            # Apply DICOM scaling for display
            rescale_slope = getattr(dicom_data, 'RescaleSlope', 1)
            rescale_intercept = getattr(dicom_data, 'RescaleIntercept', 0)
            image = (image * rescale_slope) + rescale_intercept
            
            self.current_image = image
            self.dicom_data = dicom_data
            
            self.display_image = self.normalize_image(image)
            self.original_display = self.display_image.copy()
            
            # Reset view on new image
            self.reset_view()
            print("DICOM file loaded successfully")
            
            return self.display_image, "DICOM file loaded successfully"
        except Exception as e:
            print(f"Error loading DICOM file: {str(e)}")
            return None, f"Error loading DICOM file: {str(e)}"

    def normalize_image(self, image):
        try:
            normalized = cv2.normalize(
                image, 
                None, 
                alpha=0,
                beta=255,
                norm_type=cv2.NORM_MINMAX,
                dtype=cv2.CV_8U
            )
            if len(normalized.shape) == 2:
                normalized = cv2.cvtColor(normalized, cv2.COLOR_GRAY2BGR)
            return normalized
        except Exception as e:
            print(f"Error normalizing image: {str(e)}")
            return None

    def reset_view(self):
        self.zoom_factor = 1.0
        self.pan_x = 0
        self.pan_y = 0
        if self.original_display is not None:
            return self.update_display()
        return None

    def zoom_in(self, image):
        print("Zooming in...")
        self.zoom_factor = min(20.0, self.zoom_factor + 0.5)
        return self.update_display()

    def zoom_out(self, image):
        print("Zooming out...")
        self.zoom_factor = max(1.0, self.zoom_factor - 0.5)
        return self.update_display()

    def handle_keyboard(self, key):
        try:
            print(f"Handling key press: {key}")
            pan_amount = int(5 * self.zoom_factor)
            
            original_pan_x = self.pan_x
            original_pan_y = self.pan_y
            
            if key == 'ArrowLeft':
                self.pan_x = max(0, self.pan_x - pan_amount)
            elif key == 'ArrowRight':
                self.pan_x = min(self.max_pan_x, self.pan_x + pan_amount)
            elif key == 'ArrowUp':
                self.pan_y = max(0, self.pan_y - pan_amount)
            elif key == 'ArrowDown':
                self.pan_y = min(self.max_pan_y, self.pan_y + pan_amount)
            
            print(f"Pan X: {self.pan_x} (was {original_pan_x})")
            print(f"Pan Y: {self.pan_y} (was {original_pan_y})")
            print(f"Max Pan X: {self.max_pan_x}")
            print(f"Max Pan Y: {self.max_pan_y}")
            
            return self.update_display()
        except Exception as e:
            print(f"Error handling keyboard input: {str(e)}")
            return self.display_image

    def analyze_roi(self, evt: gr.SelectData):
        try:
            if self.current_image is None:
                return None, "No image loaded"

            clicked_x = evt.index[0]
            clicked_y = evt.index[1]
            
            x = clicked_x + self.pan_x
            y = clicked_y + self.pan_y
            if self.zoom_factor != 1.0:
                x = x / self.zoom_factor
                y = y / self.zoom_factor
            
            x = int(round(x))
            y = int(round(y))
            
            height, width = self.original_image.shape[:2]
            
            Y, X = np.ogrid[:height, :width]
            
            radius = self.circle_diameter / 2.0
            r_squared = radius * radius
            
            dx = X - x
            dy = Y - y
            dist_squared = dx*dx + dy*dy
            
            mask = np.zeros((height, width), dtype=bool)
            mask[dist_squared <= r_squared] = True
            
            roi_pixels = self.original_image[mask]
            
            if len(roi_pixels) == 0:
                return self.display_image, "Error: No pixels selected"

            pixel_spacing = float(self.dicom_data.PixelSpacing[0])
            
            n_pixels = np.sum(mask)
            area = n_pixels * (pixel_spacing ** 2)
            
            mean_value = np.mean(roi_pixels)
            std_dev = np.std(roi_pixels, ddof=1)
            min_val = np.min(roi_pixels)
            max_val = np.max(roi_pixels)

            rescale_slope = getattr(self.dicom_data, 'RescaleSlope', 1)
            rescale_intercept = getattr(self.dicom_data, 'RescaleIntercept', 0)
            
            mean_value = (mean_value * rescale_slope) + rescale_intercept
            std_dev = std_dev * rescale_slope
            min_val = (min_val * rescale_slope) + rescale_intercept
            max_val = (max_val * rescale_slope) + rescale_intercept

            result = {
                'Area (mm²)': f"{area:.3f}",
                'Mean': f"{mean_value:.3f}",
                'StdDev': f"{std_dev:.3f}",
                'Min': f"{min_val:.3f}",
                'Max': f"{max_val:.3f}",
                'Point': f"({x}, {y})"
            }
            
            self.results.append(result)
            self.marks.append((x, y, self.circle_diameter))

            return self.update_display(), self.format_results()
        except Exception as e:
            print(f"Error analyzing ROI: {str(e)}")
            return self.display_image, f"Error analyzing ROI: {str(e)}"
import gradio as gr
import cv2
import numpy as np
import pandas as pd
import pydicom
import io
from PIL import Image
import openpyxl
from openpyxl.utils import get_column_letter, column_index_from_string
import logging
import time
import traceback
from functools import wraps
import sys

print("Starting imports completed...")

# Set up logging
logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('dicom_analyzer_debug.log'),
        logging.StreamHandler(sys.stdout)
    ]
)

logger = logging.getLogger(__name__)

def debug_decorator(func):
    @wraps(func)
    def wrapper(*args, **kwargs):
        logger.debug(f"Entering {func.__name__}")
        start_time = time.time()
        try:
            result = func(*args, **kwargs)
            logger.debug(f"Function {func.__name__} completed successfully")
            return result
        except Exception as e:
            logger.error(f"Error in {func.__name__}: {str(e)}")
            logger.error(traceback.format_exc())
            raise
        finally:
            end_time = time.time()
            logger.debug(f"Execution time: {end_time - start_time:.4f} seconds")
    return wrapper

class DicomAnalyzer:
    def __init__(self):
        self.results = []
        self.circle_diameter = 9.0  # Changed to float for precise calculations
        self.zoom_factor = 1.0
        self.current_image = None
        self.dicom_data = None
        self.display_image = None
        self.marks = []  # Store (x, y, diameter) for each mark
        self.original_image = None
        self.original_display = None
        # Pan position
        self.pan_x = 0
        self.pan_y = 0
        self.max_pan_x = 0
        self.max_pan_y = 0
        # Circle color in BGR
        self.CIRCLE_COLOR = (0, 255, 255)  # BGR Yellow
        print("DicomAnalyzer initialized...")

    def load_dicom(self, file):
        try:
            if file is None:
                return None, "No file uploaded"
            
            if hasattr(file, 'name'):
                dicom_data = pydicom.dcmread(file.name)
            else:
                dicom_data = pydicom.dcmread(file)
                
            image = dicom_data.pixel_array.astype(np.float32)
            
            # Store original pixel values before any scaling
            self.original_image = image.copy()
            
            # Apply DICOM scaling for display
            rescale_slope = getattr(dicom_data, 'RescaleSlope', 1)
            rescale_intercept = getattr(dicom_data, 'RescaleIntercept', 0)
            image = (image * rescale_slope) + rescale_intercept
            
            self.current_image = image
            self.dicom_data = dicom_data
            
            self.display_image = self.normalize_image(image)
            self.original_display = self.display_image.copy()
            
            # Reset view on new image
            self.reset_view()
            print("DICOM file loaded successfully")
            
            return self.display_image, "DICOM file loaded successfully"
        except Exception as e:
            print(f"Error loading DICOM file: {str(e)}")
            return None, f"Error loading DICOM file: {str(e)}"

    def normalize_image(self, image):
        try:
            normalized = cv2.normalize(
                image, 
                None, 
                alpha=0,
                beta=255,
                norm_type=cv2.NORM_MINMAX,
                dtype=cv2.CV_8U
            )
            if len(normalized.shape) == 2:
                normalized = cv2.cvtColor(normalized, cv2.COLOR_GRAY2BGR)
            return normalized
        except Exception as e:
            print(f"Error normalizing image: {str(e)}")
            return None

    def reset_view(self):
        self.zoom_factor = 1.0
        self.pan_x = 0
        self.pan_y = 0
        if self.original_display is not None:
            return self.update_display()
        return None

    def zoom_in(self, image):
        print("Zooming in...")
        self.zoom_factor = min(20.0, self.zoom_factor + 0.5)
        return self.update_display()

    def zoom_out(self, image):
        print("Zooming out...")
        self.zoom_factor = max(1.0, self.zoom_factor - 0.5)
        return self.update_display()

    def handle_keyboard(self, key):
        try:
            print(f"Handling key press: {key}")
            pan_amount = int(5 * self.zoom_factor)
            
            original_pan_x = self.pan_x
            original_pan_y = self.pan_y
            
            if key == 'ArrowLeft':
                self.pan_x = max(0, self.pan_x - pan_amount)
            elif key == 'ArrowRight':
                self.pan_x = min(self.max_pan_x, self.pan_x + pan_amount)
            elif key == 'ArrowUp':
                self.pan_y = max(0, self.pan_y - pan_amount)
            elif key == 'ArrowDown':
                self.pan_y = min(self.max_pan_y, self.pan_y + pan_amount)
            
            print(f"Pan X: {self.pan_x} (was {original_pan_x})")
            print(f"Pan Y: {self.pan_y} (was {original_pan_y})")
            print(f"Max Pan X: {self.max_pan_x}")
            print(f"Max Pan Y: {self.max_pan_y}")
            
            return self.update_display()
        except Exception as e:
            print(f"Error handling keyboard input: {str(e)}")
            return self.display_image

    def analyze_roi(self, evt: gr.SelectData):
        try:
            if self.current_image is None:
                return None, "No image loaded"

            clicked_x = evt.index[0]
            clicked_y = evt.index[1]
            
            x = clicked_x + self.pan_x
            y = clicked_y + self.pan_y
            if self.zoom_factor != 1.0:
                x = x / self.zoom_factor
                y = y / self.zoom_factor
            
            x = int(round(x))
            y = int(round(y))
            
            height, width = self.original_image.shape[:2]
            
            Y, X = np.ogrid[:height, :width]
            
            radius = self.circle_diameter / 2.0
            r_squared = radius * radius
            
            dx = X - x
            dy = Y - y
            dist_squared = dx*dx + dy*dy
            
            mask = np.zeros((height, width), dtype=bool)
            mask[dist_squared <= r_squared] = True
            
            roi_pixels = self.original_image[mask]
            
            if len(roi_pixels) == 0:
                return self.display_image, "Error: No pixels selected"

            pixel_spacing = float(self.dicom_data.PixelSpacing[0])
            
            n_pixels = np.sum(mask)
            area = n_pixels * (pixel_spacing ** 2)
            
            mean_value = np.mean(roi_pixels)
            std_dev = np.std(roi_pixels, ddof=1)
            min_val = np.min(roi_pixels)
            max_val = np.max(roi_pixels)

            rescale_slope = getattr(self.dicom_data, 'RescaleSlope', 1)
            rescale_intercept = getattr(self.dicom_data, 'RescaleIntercept', 0)
            
            mean_value = (mean_value * rescale_slope) + rescale_intercept
            std_dev = std_dev * rescale_slope
            min_val = (min_val * rescale_slope) + rescale_intercept
            max_val = (max_val * rescale_slope) + rescale_intercept

            result = {
                'Area (mm²)': f"{area:.3f}",
                'Mean': f"{mean_value:.3f}",
                'StdDev': f"{std_dev:.3f}",
                'Min': f"{min_val:.3f}",
                'Max': f"{max_val:.3f}",
                'Point': f"({x}, {y})"
            }
            
            self.results.append(result)
            self.marks.append((x, y, self.circle_diameter))

            return self.update_display(), self.format_results()
        except Exception as e:
            print(f"Error analyzing ROI: {str(e)}")
            return self.display_image, f"Error analyzing ROI: {str(e)}"