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Tensorboard Eval Images with TF-Vision
Prerequisites
Please answer the following questions for yourself before submitting an issue.
- [x] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
- [x] I am reporting the issue to the correct repository. (Model Garden official or research directory)
- [x] I checked to make sure that this issue has not been filed already.
1. The entire URL of the file you are using
https://www.tensorflow.org/tfmodels/vision/object_detection#load_logs_in_tensorboard
2. Describe the bug
I am following this documentation, https://www.tensorflow.org/tfmodels/vision/object_detection#load_logs_in_tensorboard When I open tensorboard, and select images, I get "No image data was found."
I also tried to add EXPERIMENT_CONFIG.task.allow_image_summary = True
, but I got an error, even with the dataset and code given by the documentation.
The error:
ValueError: Expected scalar shape, saw shape: (1, 640, 640, 3).
The code:
model, eval_logs = tfm.core.train_lib.run_experiment(
distribution_strategy=distribution_strategy,
task=task,
mode='train_and_eval',
params=EXPERIMENT_CONFIG,
model_dir=paths['MODEL_CHECKPOINT_PATH'],
run_post_eval=True,
)
3. Steps to reproduce
- Following this documentation: https://www.tensorflow.org/tfmodels/vision/object_detection#load_logs_in_tensorboard
- After training, open tensorboard, and select images
- See "No image data was found."
Now, try to train again with
-
EXPERIMENT_CONFIG.task.allow_image_summary = True
- see error:
ValueError: Expected scalar shape, saw shape: (1, 640, 640, 3).
4. Expected behavior
I would like to see the evaluated images per epochs saved on tensorboard.
5. Additional context
Let me know if you need anything extra
6. System information
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): MacOS 15.0
- Mobile device name if the issue happens on a mobile device: N/A
- TensorFlow installed from (source or binary): source
- TensorFlow version (use command below): v2.17.0-rc1-2-gad6d8cc177d 2.17.0
- Python version: 3.10
- Bazel version (if compiling from source): N/A
- GCC/Compiler version (if compiling from source): N/A
- CUDA/cuDNN version: N/A
- GPU model and memory: N/A -> using CPU