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Computing using Python Modules
Published in Ravishankar Chityala, Sridevi Pudipeddi, Image Processing and Acquisition using Python, 2020
Ravishankar Chityala, Sridevi Pudipeddi
Python Imaging Library (PIL) is a module for reading, writing and processing image files. It supports most of the common image formats like JPEG, PNG, TIFF, etc. In a subsequent section, PIL will be used for reading and writing images.
A video painterly stylization using semantic segmentation
Published in Journal of the Chinese Institute of Engineers, 2022
Der-Lor Way, Rong-Jie Chang, Chin-Chen Chang, Zen-Chung Shih
All experiments were run on an NVIDIA GeForce GTX 1070 GPU and an Intel Core i7-6700 CPU (an eight-core CPU clocked at 3.40 GHz). In the preprocessing stage, the Caffe training set (Jia et al. 2014) was applied in the proposed FCNs (Long, Shelhamer, and Darrell 2015) on the PASCAL VOC 2010 data sets (Everingham et al. 2010), and the YouTube-objects data set (Kalogeiton, Ferrari, and Schmid 2016) containing moving object classes in VOCs was used as a reference regarding the quality of the transferred testing videos. The Python Imaging Library was used for palette modules to colorize the segments for visualization. The style transfer model was a fully connected version of VGG-19 (Sun, Sudderth, and Black 2012) that was pretrained on the ImageNet Large Scale Visual Recognition Challenge (Russakovsky et al. 2015).
A scalable cloud-based cyberinfrastructure platform for bridge monitoring
Published in Structure and Infrastructure Engineering, 2019
Seongwoon Jeong, Rui Hou, Jerome P. Lynch, Hoon Sohn, Kincho H. Law
Similarly, Figure 9(b) shows that sequential image files collected from a traffic video camera are stored in a row by assigning timestamp (e.g. ‘2016-08-23T10:02:08’) as a clustering key. In addition, part of the timestamp (e.g. year and month) is added to the row key to partition image data to several rows based on the year and month of its acquisition. Each image file is encoded in a binary large object (BLOB) data (e.g. ‘/9j/4AAQSkZj … H//Z’) and stored in a single column. The BLOB data can be converted back to the original image file using imaging libraries, such as Python Imaging Library.4
Deep convolutional long short-term memory for forecasting wind speed and direction
Published in SICE Journal of Control, Measurement, and System Integration, 2021
Anggraini Puspita Sari, Hiroshi Suzuki, Takahiro Kitajima, Takashi Yasuno, Dwi Arman Prasetya, Abd. Rabi'
The size of output and input images were pixel. The maximum wind speed during the training dataset was slightly below 20 m/s. Therefore, the scale of plotting image by PIL (python imaging library) was set as follows, where and are the plotted point of wind data for x-axis and y-axis, respectively and 64 means half of the image size.