lannguyen0910 / food-recognition Goto Github PK

Future update for WebUI, if possible:

• https://github.com/streamlit/streamlit
• https://github.com/gradio-app/gradio

Better UX/UI and data sharing python app.

Hi! Amazing repo, and I have downloaded the code and tried to make it run from my local computer. However, the program runs into this issue that I can't seem to resolve (tried running it in Windows OS as well). I've tried online solutions to similar problems, but none of them were successful. Here is the error message I get:

Traceback (most recent call last):
File "/mnt/c/FoodImageRecognition/app.py", line 128, in
model_best = load_model('best_model_101class.hdf5', compile=False) #die
File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/saving/save.py", line 205, in load_model
return saved_model_load.load(filepath, compile, options)
File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/keras/saving/saved_model/load.py", line 122, in load
meta_graph_def = loader_impl.parse_saved_model(path).meta_graphs[0]
File "/usr/local/lib/python3.10/dist-packages/tensorflow/python/saved_model/loader_impl.py", line 116, in parse_saved_model
raise IOError(
OSError: SavedModel file does not exist at: best_model_101class.hdf5/{saved_model.pbtxt|saved_model.pb}

If you could help me resolve this issue, that would be greatly appreciated! Thank you!

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Hi, the repo is great!

The weights associated with this repo are in .pth format, usually the weights are .pt format and the pretrained weights from yolov5 repo are not working here.

Is there a way to convert the .pt weights to .pth and use with your model?

Hi!
Your repo looks amazing.
I am trying to run inference and trying to output not just a mask, but also the labels of detection as in the examples in readme file.
But somehow when I ran the inference notebook(https://drive.google.com/file/d/1CGEtC65kvoZ-4tcqzeknGrbERvb0beuU/view?usp=sharing), it only shows the mask without including the labels.

If you can help me identify what I am doing wrong, that would be helpful. Thanks!

Hello! This repo looks great. I have tested this out on my local machine, with and without ngrok. I've noticed an abnormally low accuracy, with most pictures I try resulting in an incorrect result. This is very different from the accuracy in the README, which states an accuracy of 84.069 and a balanced accuracy of 86.033. Why would this be?

Thank @kaylode and @lannguyen0910! you guys did a well-done project. I have tried to run the app notebook and found that the segmentation function is not working basically. the detection is working fine. Could you please check it out?
I see you using Unet++ from segmentation from segmentation_models.pytorch. Could you please share with me a training notebook? I find it hard to make the right setup and data preparation. I would like to understand how to implement it correctly. You can share with me via my email at [email protected]. Thank you so much!

https://github.com/kaylode/theseus/

• Loggers
• Callbacks
• Visualization

When I run the project through the python app.py, it noticed that the 'models'.yaml file is missed in 'utilities/configs' like, FileNotFoundError: [Errno 2] No such file or directory: 'utilities/configs/yolov5m.yaml' and it is also missed in './models/configs/detection' there even have no detection file under the configs path

Hi I upload food photo, press Detect and see Internal Server Error message. Please advise how could I use it. Thanks.

Hi,
Thank you for putting together this app !
I tried to run the inference notebook on Colab, but I got an error with the ngrok version:

Your ngrok-agent version "2.3.41" is too old. The minimum supported agent version for your account is "3.2.0". Please update to a newer version with `ngrok update`, by downloading from https://ngrok.com/download, or by updating your SDK version. Paid accounts are currently excluded from minimum agent version requirements. To begin handling traffic immediately without updating your agent, upgrade to a paid plan: https://dashboard.ngrok.com/billing/subscription.

ERR_NGROK_121

However, when I run ngrok update in the notebook, it says it's up to date:
!/ngrok update
No update available, this is the latest version.
Output of !/ngrok --version:
ngrok version 2.3.41

I'm not familiar with ngrok, so I don't quite know how to solve the issue right now.

Hi, this is a very impressive work! May I know the public food datasets name that you used for training the model? From the google drive, I only recognize "school lunch", where are the other training data comes from such as old_v1, vn_food? Thanks!

RuntimeError: Found no NVIDIA driver on your system. Please check that you have an NVIDIA GPU and installed a driver from http://www.nvidia.com/Download/index.aspx

Hi, this food detection project was well put together, thank you.
However, I faced some issues when running inference on Colab.

The issues i faced were when running either Yolov5 model it keeps having error, like module error (no modules named 'models'). Yolov8 works fine, but for both models when I enabled ensemble models it gives the same error, no module named 'models'. Also, in inference, it is supposed to only run on Ngrok app?

I also tried running on local machine where the port 5000 was only available to run, it worked on local machine. But the same issues arose with Yolov5 not able to run and ensemble models error.

Is there a way to solve this?
I am new to this and I am trying to learn for my upcoming project.

Thank you for your time if you could help!

I'm getting the following error after cloning the project and running pip install -e .. Any idea what might be causing this? Thanks!

ERROR: Could not find a version that satisfies the requirement opencv-python-headless==4.2.0.32 (from food-recognition) (from versions: 3.4.10.37, 3.4.11.39, 3.4.11.41, 3.4.11.43, 3.4.11.45, 3.4.13.47, 3.4.15.55, 3.4.16.57, 3.4.16.59, 3.4.17.61, 3.4.17.63, 3.4.18.65, 4.3.0.38, 4.4.0.40, 4.4.0.42, 4.4.0.44, 4.4.0.46, 4.5.1.48, 4.5.3.56, 4.5.4.58, 4.5.4.60, 4.5.5.62, 4.5.5.64, 4.6.0.66, 4.7.0.68, 4.7.0.72)
ERROR: No matching distribution found for opencv-python-headless==4.2.0.32

System Information:
Apple M1
macOS 13.1
python 3.10.6
pip 23.0.1