Problem:
‘Undefined Symbol: PySlice_Unpack’
Environment:
Pytorch = 1.0.1 Python = 3.6.0 Solution:
Upgrade Python to 3.6.3. Seems like this is the only solution.
Update by conda install python==3.6.3 command if using Miniconda in CLI.
This notebook presents a data preparation workflow that finds same-date and overlapped Landsat8 and Sentinel2 image patches and provide a way to download the processed images to the local machine.
This is a part of the ongoing research project Landsat2Sentinel.
The whole notebook is available on my Github repository.
import ee ee.Initialize() from IPython import display import zipfile import urllib from ipywidgets import IntProgress Function for downloading images from GEE def download_tif(image, scale, name, folder): url = ee.
Recently, during a discussion with a colleague about his CNN model architecture on remote sensing image fusion task, he mentioned something that was interesting. Specifically, in his network, he used FCN implementations Keras.layers.Dense and torch.nn.Linear in his code, the input to the FCN is a 2D image with many channels with size (160, 160, channels). Traditionally, I think that to pass through a FCN layer, the neuron numbers of the first FCN layer in this case, should be 160 * 160 * channels, which basically means to flat the volume to a 1D array and feed in a traditional neural network.
Recently I have completed the 5-month journey of the Deep Learning specialization on Coursera. I enjoyed this course a lot.
Can’t wait to apply some of the idea in my research work. Cheers!
Good job for me to earn several deep learning related certificates under the Deep Learning Specialization on Coursera. The specialization is offered by Dr. Andrew Ng from deeplearning.ai.
The course assignments can be found at https://github.com/zhiqiyu/Deep-Learning-Coursera
Following is the breakdown course certificates I earned.