Retour à Deep Learning with PyTorch : Image Segmentation
Avis et commentaires pour d'étudiants pour Deep Learning with PyTorch : Image Segmentation par Coursera Project Network
À propos du cours
In this 2-hour project-based course, you will be able to :
- Understand the Segmentation Dataset and you will write a custom dataset class for Image-mask dataset. Additionally, you will apply segmentation augmentation to augment images as well as its masks. For image-mask augmentation you will use albumentation library. You will plot the image-Mask pair.
- Load a pretrained state of the art convolutional neural network for segmentation problem(for e.g, Unet) using segmentation model pytorch library.
- Create train function and evaluator function which will helpful to write training loop. Moreover, you will use training loop to train the model.
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1 - 1 sur 1 Avis pour Deep Learning with PyTorch : Image Segmentation
par Shane M
•21 nov. 2021
Pretty good overall. Some work needed with this projects to make them easier to debug, such as making source code available with a diff tool so people can more easily pick out stupid types.
Because this is python, not cpp or java or similar, it can actually be pretty hard to catch a lot of typos, due to lack of compile time checks, scope control, and abundance of global variables.
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