I am unable to create a tfrecord and there is no error in the code, it was just executing when i have given this code
python generate_tfrecords.py --csv_input=images\train_labels.csv --image_dir=images\train --output_path=train.record
i have also checked the image files all are in one folder and with the same format.
please help to create the tfrecord
Thanking you
created a images using labelImg and also did the protobuf part
there are no error but it was not creating a train record
Related
There is this file (events.out.tfevents.1611631707.8f60fbcf7419.profile-empty) that appears alongside other files e.g. events.out.tfevents.1611897478.844156cf4a75.61.560.v2.
My model training is not going well at all so I am looking all over to identify things I don't understand to see if they may be the cause. What is this .profile-empty file for? An image below to show the files.
This is a file written by the TensorFlow profiler. It is here to help the TensorBoard know which directory contains the profile data.
From the commit c66b603:
save empty event file in logdir when running profiler. TensorBoard will use this event file to identify the logdir that contains profile data
And from the commit 23d8e38:
Save an empty event file when StartTracing is called. This is to help with TensorBoard subdirectory searching.
I'm trying to train a new object detection model using the Create ML tool from Apple. I've already used RectLabel to generate annotations for all of the JPEG images in my directory of training images.
However, every time I try loading the directory in Create ML, I receive this error message:
Empty table from specified data source
I already looked on the Apple Developer forums and that thread incorrectly claims the problem was solved in a previous update.
What causes this error? How can I get Create ML to accept my training data?
I'm using Create ML Version 2.0 (53.2.2) and RectLabel Version 3.04.2 (3.04.2) on macOS Big Sur 11.0.1 (20B29).
The “Empty table from specified data source” error occurs if any of the filenames contain spaces.
My solution was to rename all the files so the filenames don't contain spaces.
Make sure that there are only images and annotations.json file in your directory of training images.
If there are any other files including .mlproj file in the folder, Create ML shows the "Empty table from specified data source" error.
When you create a new project on Create ML, specify outside the directory of training images.
How can I download all the input data from a kaggle kernel? For example this kernel: https://www.kaggle.com/davidmezzetti/cord-19-study-metadata-export.
Once you make a copy and have the option to edit, you have the ability to run the notebook and make changes.
One thing I have noticed is that anything that goes in the output directory is provided with an option of a download button next to the file icon. So I see that I can surely just read each and every file and write to the output but it seems like a waste.
Am I missing something here?
The notebook you list contains two data sources;
another notebook (https://www.kaggle.com/davidmezzetti/cord-19-analysis-with-sentence-embeddings)
and a dataset (https://www.kaggle.com/allen-institute-for-ai/CORD-19-research-challenge)
You can use Kaggle's API to retrieve a kernel's output:
kaggle kernels output davidmezzetti/cord-19-analysis-with-sentence-embeddings
And to download dataset files:
kaggle datasets download allen-institute-for-ai/CORD-19-research-challenge
I am using Google Vision Automl. In order to train a model the data needs to be uploaded. There are following two ways.
Upload directly from your computer
Upload to google bucket and make a csv which contains the paths to the image files.
See the following image
Since, i want to compare my locally pre-trained model with the model i will train on Google Automl, i want to ensure that the same data splits are used (train, test, validation). So #2 way is the best way
Issue:
I have made a the csv in the following format. But when i upload it, only train and test sets are loaded.
I solved it by putting "Validation" instead of "Validate" in the set column.
So the issue was the language used on the upload form, where they have the following.
Optionally, you can specify the TRAIN, VALIDATE, or TEST split.
Which is misleading and they also did not show the sample row for Validation.
For more details:
https://cloud.google.com/vision/automl/docs/prepare#csv
I've been trying to run the object_detection_tutorial located at https://github.com/tensorflow/models/tree/master/research/object_detection but keep getting an error when trying to load the model.
I get:
INFO:tensorflow:Saver not created because there are no variables in the graph to restore
when i try to do:
tf.saved_model.load(model_dir)
I've gone through the installation instructions and done all of that but I can't load the model. Anyone have any idea? Thanks.