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دانلود کتاب Python Image Processing Cookbook
دانلود کتاب کتاب آشپزی پردازش تصویر پایتون
مشخصات کتاب
Python Image Processing Cookbook
ویرایش: سری: ISBN (شابک) : 9781789537147 ناشر: سال نشر: تعداد صفحات: 429 زبان: فرمت فایل : PDF (درصورت درخواست کاربر به PDF، EPUB یا AZW3 تبدیل می شود) حجم فایل: 96 مگابایت
قیمت کتاب (تومان) : 75,000
در صورت تبدیل فایل کتاب Python Image Processing Cookbook به فرمت های PDF، EPUB، AZW3، MOBI و یا DJVU می توانید به پشتیبان اطلاع دهید تا فایل مورد نظر را تبدیل نمایند.
توجه داشته باشید کتاب کتاب آشپزی پردازش تصویر پایتون نسخه زبان اصلی می باشد و کتاب ترجمه شده به فارسی نمی باشد. وبسایت اینترنشنال لایبرری ارائه دهنده کتاب های زبان اصلی می باشد و هیچ گونه کتاب ترجمه شده یا نوشته شده به فارسی را ارائه نمی دهد.
توضیحاتی در مورد کتاب کتاب آشپزی پردازش تصویر پایتون
پیشرفتها در دستگاههای بیسیم و فنآوری تلفن همراه، امکان دستیابی به حجم عظیمی از گرافیک، عکس و ویدیو را فراهم کرده است. این کتاب از طریق دستور العمل های پیشرفته، ابزارها، الگوریتم ها و تجزیه و تحلیل پردازش تصویر را پوشش می دهد. این کتاب راه حل هایی برای پرداختن به چالش ها و وظایف پیچیده پردازش تصویر ارائه می دهد.
توضیحاتی درمورد کتاب به خارجی
Advancements in wireless devices and mobile technology have enabled the acquisition of a tremendous amount of graphics, pictures, and videos. Through cutting edge recipes, this book provides coverage on tools, algorithms, and analysis for image processing. This book provides solutions addressing the challenges and complex tasks of image processing.
فهرست مطالب
Cover Title Page Copyright and Credits About Packt Dedication Contributors Table of Contents Preface Chapter 1: Image Manipulation and Transformation Technical requirements Transforming color space (RGB → Lab) Getting ready How to do it... Converting RGB image into grayscale by setting the Lab space color channels to zero Changing the brightness of the image by varying the luminosity channel How it works... There's more... Applying affine transformation Getting ready How to do it... How it works... There's more... Applying perspective transformation and homography Getting ready How to do it... How it works... There's more... See also Creating pencil sketches from images Getting ready How to do it... How it works... There's more... See also Creating cartoonish images Getting ready How to do it... How it works... There's more... See also Simulating light art/long exposure Getting ready How to do it... How it works... There's more... Extended depth of field with mahotas See also Object detection using color in HSV Getting ready How to do it... How it works... See also Chapter 2: Image Enhancement Applying filters to denoise different types of noise in an image Getting ready How to do it... How it works... There's more... Image denoising with a denoising autoencoder Getting ready How to do it... How it works... There's more... See also Image denoising with PCA/DFT/DWT Getting ready How to do it... How it works... There's more... See also Image denoising with anisotropic diffusion Getting ready How to do it... How it works... There's more... See also Improving image contrast with histogram equalization Getting ready How to do it... How it works... There's more... Implementing histogram matching Getting ready How to do it... How it works... There's more... See also Performing gradient blending Getting ready How to do it... How it works... Edge detection with Canny, LoG/zero-crossing, and wavelets Getting ready How to do it... Canny/hysteresis thresholding LoG/zero-crossing Wavelets How it works... There's more... See also Chapter 3: Image Restoration Restoring an image with the Wiener filter Getting ready How to do it... How it works... See also Restoring an image with the constrained least squares filter Getting ready How to do it... How it works... There's more... See also Image restoration with a Markov random field Getting ready How to do it... How it works... See also Image inpainting Getting ready How to do it... How it works... There's more... Image inpainting with convex optimization See also Image completion with inpainting using deep learning Getting ready How to do it... There's more... See also Image restoration with dictionary learning Getting ready How to do it ... There's more... Online dictionary learning See also Compressing an image using wavelets Getting ready How to do it... How it works... See also Using steganography and steganalysis Getting ready How to do it... How it works... There's more... See also Chapter 4: Binary Image Processing Applying morphological operators to a binary image Getting ready How to do it... How it works... There's more... See also Applying Morphological filters Getting ready How to do it... Computing the Euler number, eccentricity, and center of mass with mahotas/scikit-image Morphological image filters with mahotas Binary image filters with SimpleITK Dilation by reconstruction with skimage How it works... There's more... See also Morphological pattern matching Getting ready How to do it... How it works... There's more... See also Segmenting images with morphology Getting ready How to do it... Morphological watershed Blob detection with morphological watershed How it works... There's more... Blob detection with LOG scale-space See also Counting objects Getting ready How to do it... Blob separation and detection with erosion Object counting with closing and opening How it works... There's more... See also Chapter 5: Image Registration Medical image registration with SimpleITK Getting ready How to do it... How it works... There's more See also Image alignment with ECC algorithm and warping Getting ready How to do it... How it works... There is more See also Face alignment with dlib Getting ready How to do it... How it works... There is more See also Robust matching and homography with the RANSAC algorithm Getting ready How to do it... How it works... See also Image mosaicing (panorama) Getting ready How to do it... Panorama with OpenCV-Python How it works... There is more See also Face morphing Getting ready How to do it... How it works There is more See also Implementing an image search engine Getting ready How to do it... Finding similarity between an image and a set of images with SIFT Steps to implement a simple image search engine There is more See also Chapter 6: Image Segmentation Thresholding with Otsu and Riddler–Calvard Getting ready How to do it... How it works... There's more... See also Image segmentation with self-organizing maps Getting ready How to do it... How it works... There's more... Clustering handwritten digit images with SOM See also RandomWalk segmentation with scikit-image Getting ready How to do it... How it works... There's more... See also Human skin segmentation with the GMM-EM algorithm Getting ready How to do it... How it works... See also Medical image segmentation Getting ready How to do it... Segmentation with GMM-EM Brain tumor segmentation using deep learning Segmentation with watershed How it works... There's more... See also Deep semantic segmentation Getting ready How to do it... Semantic segmentation with DeepLabV3 Semantic segmentation with FCN See also Deep instance segmentation Getting ready How to do it... How it works... See also Chapter 7: Image Classification Classifying images with scikit-learn (HOG and logistic regression) Getting ready How to do it... How it works... There's more... See also Classifying textures with Gabor filter banks Getting ready How to do it... How it works... There's more... See also Classifying images with VGG19/Inception V3/MobileNet/ResNet101 (with PyTorch) Getting ready How to do it... How it works... There's more... See also Fine-tuning (with transfer learning) for image classification Getting ready How to do it... How it works... There's more... See also Classifying traffic signs using a deep learning model (with PyTorch) Getting ready How to do it... How it works... There's more... See also Estimating a human pose using a deep learning model Getting ready How to do it... How it works... See also Chapter 8: Object Detection in Images Object detection with HOG/SVM Getting started How to do it... How it works... There's more... See also Object detection with Yolo V3 Getting started How to do it... How it works... There's more... See also Object detection with Faster R-CNN Getting started How to do it... How it works... There's more... See also Object detection with Mask R-CNN Getting started How to do it... How it works... There's more... See also Multiple object tracking with Python-OpenCV Getting started How to do it... How it works... There's more... See also Text detection/recognition in images with EAST/Tesseract Getting started How to do it... How it works... See also Face detection with Viola-Jones/Haar-like features Getting ready How to do it... How it works... There's more... See also Chapter 9: Face Recognition, Image Captioning, and More Face recognition using FaceNet Getting ready How to do it... How it works... See also Age, gender, and emotion recognition using deep learning models Getting ready How to do it... There's more... See also Image colorization with deep learning Getting ready How to do it... See also Automatic image captioning with a CNN and an LSTM Getting ready How to do it... How it works... See also Image generation with a GAN Getting ready How to do it... How it works... There's more... See also Using a variational autoencoder to reconstruct and generate images Getting ready How to do it... There's more... See also Using a restricted Boltzmann machine to reconstruct Bangla MNIST images Getting ready How to do it... See also Other Books You May Enjoy Index
