I'm a beginner with PyTorch and I'm trying to download the MNIST dataset using PyTorch with the following code:
torchvision.datasets.MNIST('data/', download=True)
This succeeds by downloading the raw files. But there is no 'processed' folder containing the training.pt and test.pt files.
How do I generate them?
I tried to add options like train=True or transform=torchvision.transforms.ToTensor to the code. But there files are not generated.
Related
I am trying to use the Open Images dataset to train a binary CNN model (Orange vs. Not Orange).
I use the OID v4 toolkit to download images of few classes both in train and test.
Now I'm stuck with how to conert the multiclass shape in each directory to a binary.
I believe I need some tool to change the subfolders (=classes) name.
I've succeeded using os and shutil packages to manipulate the directories as requested.
TXS.
I recently convert my model to tensorflow lite but I only got the .tflite file and not a labels.txt for my Android project. So is it possible to create my own labels.txt using the classes that I used to classify? If not, then how to generate labels.txt?
You should be able to generate and use your own labels.txt. The file needs to include the label names in the order you provided them in training, with one name per line.
Run the following code after installing the TFLite Model Maker library and pass the dataset for classification:
data = ImageClassifierDataLoader.from_folder('folder/')
train_data, test_data = data.split(0.8)
model = image_classifier.create(train_data)
loss, accuracy = model.evaluate(test_data)
model.export('image_classifier.tflite', 'imageLabels.txt')
On running it in Colab or locally, the labels files would be auto-generated with the categories from each of the subfolders.
I need to train tensorflow deeplab model with my shoes dataset. Then i will use this model in order to remove background of image shoe. How could i train it ? Could you explain step by step ? You have any example for this situation ?
tensorflow/deeplab
You will need read some parts of Deeplab code
Download repo
Now you need to put your data in tfrecord in proper format
Use some of scripts in https://github.com/tensorflow/models/tree/master/research/deeplab/datasets to download and generate example datasets
Prepare analogous script for your shoes dataset
Add information about data to Deeplab source file https://github.com/tensorflow/models/blob/master/research/deeplab/datasets/data_generator.py add info in analogous format like example datasets
Check flags for architecture https://github.com/tensorflow/models/blob/master/research/deeplab/common.py
Check specific flags and then train, export, count statistics or visualize using train.py, vis.py, export_model.py, eval.py in folder https://github.com/tensorflow/models/tree/master/research/deeplab
I have trained a deep learning model using tensorflow and i saved it as an "cnn.h5" file using keras. Now I have 3 files that have "cnn.h5" in their name but all of them contain a different extension. The three files are:
cnn.h5.meta
cnn.h5.index
CNN.h5.data-00000-of-00001
now can anyone tell me which one of the above files is the saved model? i have to load that model in my GUI for testing.
Thanks.
This blog post explains saving and restoring you can refer to it for details a snippet of explanation for the type of saved files is as below.
When saving the model, you'll notice that it takes 4 types of files to save it:
".meta" files: containing the graph structure
".data" files: containing the values of variables
".index" files: identifying the checkpoint
I need to train from scratch a CNN over a COCO dataset with a specific configuration: https://github.com/tensorflow/models/blob/master/research/object_detection/samples/configs/embedded_ssd_mobilenet_v1_coco.config
Thus, I installed TF Object Detection API and I downloaded the COCO dataset. However the dataset is in .h5 extension.
Is it possible to run the training with this kind of file or do I need to convert it in images in someway? If that is possible, what would the command be?
PS: I was not able to find a pre-trained model with that config, this is why I need to train a cnn from scratch.
My suggestion would be to convert the .hdf5 file to a .tfrecord file, you can find examples of how to do this here.