I tried tflite-model-maker before, and it was working fine however, recently I’ve been encountering an error when tried installing the tflite-model-maker in colab.
ERROR: Could not find a version that satisfies the requirement tflite-support>=0.4.2 (from tflite-model-maker) (from versions: 0.1.0a0.dev3, 0.1.0a0.dev4, 0.1.0a0.dev5, 0.1.0a0, 0.1.0a1)
ERROR: No matching distribution found for tflite-support>=0.4.2 (from tflite-model-maker)
ERROR: Could not find a version that satisfies the requirement opencv-python-headless==220.127.116.11 (from versions: 18.104.22.168, 22.214.171.124, 126.96.36.199, 188.8.131.52, 184.108.40.206, 220.127.116.11, 18.104.22.168, 22.214.171.124, 126.96.36.199, 188.8.131.52, 184.108.40.206, 220.127.116.11, 18.104.22.168, 22.214.171.124, 126.96.36.199, 188.8.131.52, 184.108.40.206, 220.127.116.11, 18.104.22.168, 22.214.171.124, 126.96.36.199, 188.8.131.52, 184.108.40.206, 220.127.116.11, 18.104.22.168)
ERROR: No matching distribution found for opencv-python-headless==22.214.171.124
May I know how I can fix this? Every time I run it again, the error changes among tflite-support → scann → numba → goes back to tflite-support.
Thank you for reporting the issue. We will check and get back to you.
According to Colab Updated to Python 3.10:
Colab’s fallback runtime version: Using the fallback runtime version temporarily allows access to the Python 3.9 runtime, and will be available until mid-May. This is available from the Command Palette via the
Use fallback runtime version command when connected to a runtime. Of note, this setting does not persist across sessions — the command will need to be invoked on each new session.
As a temporary workaround, you can use the Colab fallback runtime version option to choose Python 3.9 and install
tflite-model-maker. By doing this you will get
RuntimeError and it can be ignored.
To access the command palette in Colab, presss cmd+shift+P and then type
Use fallback runtime version and select it.
By following the above process, i am successfully able to execute Model Maker Image Classification Tutorial.
Thank you very much it seems to be running now.
Will this be resolved in time for fallback to expire in mid may?
hi, I encountered the same problem and the temporary fix to use Python 3.9 runtime is already unavailable in May 24. Is there any way I can use the command
!pip install -q tflite-model-maker?
i have the same problem the temporary fix to use Python 3.9 runtime is already unavailable. is there any other solution ??
@wifek_maghraoui @18219102_Kristofer_H ,
TF Lite development team are working on it.
You can try to use the MediaPipe Model Maker.
Does MediaPipe support EfficientDet-Lite custom training?
Hi, Can you please tell me how much time this issue takes to get fixed?
Are there any timelines/thread we can follow to keep updated with this?
Guys, I am happy to inform you that you can use virtual environment for installing tflite-model-maker
I didn’t find how to use it in colab notebook, but you can use bash commands for installation and trainining models (put your code in .py and run python code.py) , anyway it’s better than nothing.
python3.8 -m virtualenv venv
virtualenv --python=/usr/bin/python3.8 liteenv
pip install --upgrade pip==20.1.1
pip install tensorflow==2.8.0
git clone https://github.com/tensorflow/examples
pip3 install -e .
// fix some dependencies. may differ for you
pip3 install protobuf==3.20.0 numpy==1.20.3
Hello thank you for updating the solution. Have you tried training custom model after this fix. If yes please share the steps here.