Tensorflow 2 Custom Object Detection Model (Google Colab and Local PC)
Tensorflow is an open-source machine learning framework developed by Google. It is widely used for various machine learning and deep learning tasks, including object detection. Tensorflow 2 is the latest version of the framework and comes with a variety of improvements and new features.
Custom Object Detection Model
Object detection is the process of identifying and locating objects in images or videos. While Tensorflow provides pre-trained models for object detection, sometimes we may need to create a custom object detection model for specific use cases. This can be achieved using Tensorflow 2 and its powerful API.
Google Colab
Google Colab is a free cloud-based Jupyter notebook environment provided by Google. It allows users to write and execute Python code using various libraries including Tensorflow. With Google Colab, you can easily create and train custom object detection models using Tensorflow 2 without the need for a powerful local PC.
Local PC
If you prefer to work on your local PC, you can also create and train custom object detection models using Tensorflow 2. You will need to have a good understanding of Python and the necessary hardware resources for training large models.
Getting Started
To get started with creating a custom object detection model using Tensorflow 2, you can follow the official documentation provided by Google. This will guide you through the process of setting up your environment, preparing your dataset, creating the model architecture, and training the model.
Conclusion
Creating custom object detection models using Tensorflow 2 can be a challenging but rewarding task. Whether you choose to use Google Colab or your local PC, Tensorflow 2 provides the tools and resources needed to build powerful and efficient models for object detection.
i have followed all the steps but lot of error is showing this is one of the example error
slim = tf.contrib.slim
AttributeError: module 'tensorflow' has no attribute 'contrib'
i wasted my time trying to refollow every single step in this tutorial but now help their is so many error wasted my time on this tutorial no help at all just look for another tutorial that might actually help you
please answer where can i access the config fiels that you edit
you are showing about the config files but we dont have access to those.. where can i get those config files
where can i get the configs
Is anyone else getting "AttributeError: module 'tensorflow.python.ops.control_flow_ops' has no attribute 'case'"?
I run the code in the collab and last step !python /content/models/research/object_detection/model_main_tf2.py gives that error:( And I cannot downgrade tensorflow version on Collab to anything less than 2.8.0…
AttributeError: in user code:
File "/usr/local/lib/python3.10/dist-packages/object_detection/data_decoders/tf_example_decoder.py", line 556, in decode *
tensors = decoder.decode(serialized_example, items=keys)
File "/usr/local/lib/python3.10/dist-packages/tf_slim/data/tfexample_decoder.py", line 722, in decode *
outputs.append(handler.tensors_to_item(keys_to_tensors))
File "/usr/local/lib/python3.10/dist-packages/tf_slim/data/tfexample_decoder.py", line 405, in tensors_to_item *
return self._decode(image_buffer, image_format)
File "/usr/local/lib/python3.10/dist-packages/tf_slim/data/tfexample_decoder.py", line 453, in _decode *
image = control_flow_ops.case(
AttributeError: module 'tensorflow.python.ops.control_flow_ops' has no attribute 'case'
will the roboflow dataset work if I export it as tensorflow TFrecord and use it in the notebook?
I got error at "import tensorflow.compat.v2 as tf"
please help
If anyone is encountering this error:
TypeError: __init__(): incompatible constructor arguments. The following argument types are supported: 1. tensorflow.python.lib.io._pywrap_file_io.BufferedInputStream(filename: str, buffer_size: int, token: tensorflow.python.lib.io._pywrap_file_io.TransactionToken = None)
I solved mine by shortening the config file filename
Your tutorial is amazing straightforward and saved me a lot of headache looking through other tutorials. I have a question, would you happen to know how to export to tflite format for object detection for RaspPi. Been trying to figure this out but to no avail.
I personally don't prefer google colab if you're a free user. It will be extremely slow, so in short use your pc if you're a free user.
Idk if you can help me but I am getting the following error when I run the training script: Tensorflow: AttributeError: module 'tensorflow.python.ops.control_flow_ops' has no attribute 'case'
I appreciated your tutorial and I definitely learned a lot from you. Keep it going, we're here to support you.
import tensorflow.compat.v2 as tf
ModuleNotFoundError: No module named 'tensorflow.compat'
Hi sir, my project had this error and I can't find solution for that
Does the colab notebook still work? As I've encountered in my other projects, the object_detection API won't install. Also, Tensorflow==2.6.0 is not available.
If I want to use dataset from roboflow universe ,which format should I choose?And what is next step I need to do?
Hope someone can help me🙏🙏🙏
can we deploy our trained model to local host or website to detect image from uploaded image ?
Has anyone had a similar problem? 'self._read_buf = _pywrap_file_io.BufferedInputStream(
UnicodeDecodeError: 'utf-8' codec can't decode byte 0xbf in position 100: invalid start byte'
This is the best and clean tutorial I have seen so far. Thank you.
Youtube should provide zoom option for this video, My eyes are paining after watching this video very closely.