Amro Ghoneim
Amro Ghoneim
Hey, while I hope someone answers this, can you point me to how you used supervisor with gunicorn to do the logging?
This is how the loss looks like within the sample elbo method for multiple samples over many epochs PERFORMANCE LOSS: 1.3859792947769165 PERFORMANCE + KL LOSS: 446.3642578125 PERFORMANCE LOSS: 447.8734436035156 PERFORMANCE...
@MissPenguin Please advise.
@huynhkhoa44 We did eventually use our own detection model. We made sure to send the output of that model to have the same format needed by the recognize method input...
You need to remove the following lines from ```easyocr.py``` ``` # elif calculate_md5(model_path) != model['md5sum']: # if not self.download_enabled: # raise FileNotFoundError("MD5 mismatch for %s and downloads disabled" % model_path)...
These lines just check if this model is equivalent( same weights, architecture everything) to the what have in their storage. Since we retrained the model, the weights will change, so...
Interesting. So checking out the zip file mentioned, custom_example.pth would be best_accuracy.pth custom_example.py would be model.py and custom_example.yaml would be the config file used for training using only the parameters...
``` user_network_directory (bool, default = None) - Path to user-defined recognition network. If not specified, models will be read from MODULE_PATH + '/user_network' (~/.EasyOCR/user_network). recog_network (string, default = 'standard') -...
Facing the same issue too still.
@rkcosmos can you please check this out and give us any advice?