The D Programming Language - Digitalmars-d
March 2025 Archives by thread
Starting: Sat Mar 1 22:30:54 UTC 2025
Ending: Mon Mar 31 23:16:57 UTC 2025
Messages: 380
- Managing Postgraduate Nursing Education to Improve Patient Care
Labiteb Will
- Whats worth taking from "railroad oriented programming"
Inkrementator
- What _is_ up with v2.110?
FeepingCreature
- Applying Placement New to druntime and phobos
Per Nordlöw
- MP4 Library
Ron Tarrant
- How should to!string handle infinite ranges?
Paul Backus
- Future of SafeRefCounted
Derek Fawcus
- A big update on 2.110
Dennis
- Problem with GC and address/leak sanitizer
Luís Marques
- dub-registry search should include sub-packages
Element Green
- DMD AArch64 progress
Walter Bright
- D Style document
Dejan Lekic
- Gamut v3.3 brings niche SQZ codec support
Guillaume Piolat
- CI seems to have regressed?
Manu
- TypeScript is being ported to Go | interview with Anders Hejlsberg
Robert Schadek
- Please improve the with statement by allowing initialisation
Dejan Lekic
- Making 2024 the Year of D
Sergey
- Enhancement on `export` symbol
Hipreme
- “Out” parameters and destructors
Ogion
- Generating enum members
Milli
- How to fix issue#10636 ?
Aditya
- Why is database management an essential factor for hiring ASP.NET developers?
Ben Roy
- import cv2 import numpy as np import matplotlib.pyplot as plt # Function to load and preprocess the image def preprocess_image(image_path): # Read the image in grayscale img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE) # Apply Gaussian Blur to reduce noise img_blurred = cv2.GaussianBlur(img, (5, 5), 0) # Apply adaptive thresholding to detect bands _, thresh_img = cv2.threshold(img_blurred, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU) return thresh_img # Function to detect bands in the gel def detect_bands(thresh_img): # Find contours in the thresholded image (these correspond to the bands) contours, _ = cv2.findContours(thresh_img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) # Filter small contours that may be noise bands = [cnt for cnt in contours if cv2.contourArea(cnt) > 100] return bands # Function to plot the bands def plot_bands(image_path, bands): # Load the original image for visualization img = cv2.imread(image_path) # Draw the detected bands on the image img_bands = img.copy() for band in bands: cv2.drawContours(img_bands, [band], -1, (0, 255, 0), 2) # Convert the image from BGR to RGB for matplotlib img_bands_rgb = cv2.cvtColor(img_bands, cv2.COLOR_BGR2RGB) # Display the image with detected bands plt.imshow(img_bands_rgb) plt.axis('off') plt.show() # Function to measure the intensity of bands def measure_band_intensity(image_path, bands): img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE) intensities = [] for band in bands: # Create a mask for each band mask = np.zeros_like(img) cv2.drawContours(mask, [band], -1, 255, thickness=cv2.FILLED) # Calculate the average intensity inside the band mask band_intensity = cv2.mean(img, mask)[0] intensities.append(band_intensity) return intensities # Main program if __name__ == "__main__": # Path to the gel electrophoresis image image_path = 'gel_image.jpg' # Change this to your image file path # Preprocess the image thresh_img = preprocess_image(image_path) # Detect bands in the image bands = detect_bands(thresh_img) # Plot the bands on the original image plot_bands(image_path, bands) # Measure the intensity of each detected band intensities = measure_band_intensity(image_path, bands) # Display the intensity values for each band for i, intensity in enumerate(intensities): print(f"Band {i+1} intensity: {intensity}")
devendra bairwa
- Tsoding streamed about D
Maximilian Naderer
- Poll: what should this program do?
Paul Backus
- LDC command arguments vs DMD argument
Derek Fawcus
- Where Can I Find Test Data and How to Use It for Testing?
james alary
- [OT] Evolving Scala
Sergey
- Internationalization support and format strings
Bruno Haible
- LLM's think we should have language tuples!
Manu
- 🚀 ¿Qué opinan de usar D en Inteligencia Artificial?
daniel
- operator overloading outside the type
Steven Schveighoffer
- Tsoding - How Not to Market Your Language Features
Ali Çehreli
- Using the sundials solver package from D - my first experience with importC
Robert Kovacs
- React vs. Vue vs. Angular – Which One to Choose?
henry wagner
- Order of evaluation for named arguments
Steven Schveighoffer
- Build in associated array (DIctionary) needs some enhancements
An Pham
- Scope guards style guide
Elias Batek (0xEAB)
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Mon Mar 31 23:16:57 UTC 2025
Archived on: Mon Mar 31 23:20:03 UTC 2025
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