Tensorflow-object-detection | Detect different objects in an image using SSD | Computer Vision library

I am following this tutorial https://github.com/EdjeElectronics/TensorFlow-Object-Detection-API-Tutorial-Train-Multiple-Objects-Windows-10.

System - Windows 10, Anaconda Prompt, Python 3.6, tensorflow 1.15.0

Initial setup and training are successful. Upon pausing the training and resuming I get the error message from the title. Any help would be greatly appreciated.

I'm trying debug my trained Faster R-CNN model using Tensorflow Object Detection API and I want to visualize the proposal regions of RPN on an image. Can anyone tell me how to do it? I found a post here but it hasn't been answered. I tried to export the model using exporter_main_v2.py with only the RPN head as said here and this is the massage when I deleted the second_stage.

I am working on an object detection model in google colab and I'm following most of the instructions outlined here.

In order to train the model, I am trying to use:

While running models/research/object_detection/model_main_tf2.py from tensorflow/models (or just python -c "from object_detection import model_lib_v2") I get:

I followed the "Training Custom Object Detector" tutorial (https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html)

When running the script to continue training a pre-trained model:

python model_main_tf2.py --model_dir=models/my_ssd_resnet50_v1_fpn --pipeline_config_path=models/my_ssd_resnet50_v1_fpn/pipeline.config

(found here: https://github.com/tensorflow/models/blob/master/research/object_detection/model_main_tf2.py)

Using different numpy versions, I get the following errors.

Scenario #1:

• tensorflow: 2.2.0
• numpy: 1.20.0-1

NotImplementedError: Cannot convert a symbolic Tensor (cond_2/strided_slice:0) to a numpy array. This error may indicate that you're trying to pass a Tensor to a NumPy call, which is not supported

I looked online and it suggests to downgrade the numpy version < 1.20.0 (NotImplementedError: Cannot convert a symbolic Tensor (2nd_target:0) to a numpy array). Note, the version numpy version must be >= 1.19.2 for tensorflow 2.2.0.

Scenario #2:

• tensorflow: 2.2.0
• numpy: 1.19.2-5

ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject

However, the online recommendation is to upgrade numpy to >= 1.20.0. (ValueError: numpy.ndarray size changed, may indicate binary incompatibility. Expected 88 from C header, got 80 from PyObject). There is a github issue related to this: https://github.com/tensorflow/models/issues/9749.

I'm not sure what version to use to get the code running.

Appendix: Scenario #1 Error Code (numpy: 1.20.0-1)

I ran through the TensorFlow object detection installation on Windows.

https://medium.com/riow/tensorflow-object-detection-on-windows-ad10bfde217c

After successfully installing TensorFlow object detection,

I ran following command to test, and receiving error below. How can this be fixed?

I am trying to install Tensor Flow Object Detection on Windows 10.

Resource: https://towardsdatascience.com/how-to-install-tensorflow-2-object-detection-api-on-windows-2eef9b7ae869

After running these steps, we are receiving the errors below. It is stalling on pyarrow. How can this be fixed?

I try to train a model object detection and I follow this tutorial: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/tensorflow-1.14/training.html

But at the end I execute the command in the cmd : python model_main.py --alsologtostderr --model_dir=training/ --pipeline_config_path=training/ssd_inception_v2_coco.config

and it return the following lines:

For utilizing Tensorflow's Object Detection transfer learning capabilities, I followed the "Training Custom Object Detector" tutorial (https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/latest/training.html)

When running the script to continue training a pre-trained model:

python model_main_tf2.py --model_dir=models/my_ssd_resnet50_v1_fpn --pipeline_config_path=models/my_ssd_resnet50_v1_fpn/pipeline.config

(found here: https://github.com/tensorflow/models/blob/master/research/object_detection/model_main_tf2.py)

It would give the error failed to create cublas handle: CUBLAS_STATUS_ALLOC_FAILED and Could not create cudnn handle: CUDNN_STATUS_ALLOC_FAILED.

Appendix: Full Error Message.