Comments (2)
suraj-deshmukh
commented on June 29, 2024
the network configuration and loss function worked for my problem statement that doesn't necessarily mean it should work for any type of problem statement. Try with bigger network but loss function won't change as it is a multi label classification matrix and try with different optimization technique and you can add your own evaluation metric while tranining.
for your reference:
https://keras.io/metrics/
from keras-multi-label-image-classification.
wpl18589946597
commented on June 29, 2024
I use the vgg16 network to retrain my data, I found that the complete result for test data is zero,
from keras-multi-label-image-classification.
Related Issues (18)
- You should use binary_accuracy instead of accuracy
- Getting 404 for https://suraj-deshmukh.github.io/Multi-Label-Image-Classification/ HOT 1
- what does best_threshold mean๏ผ HOT 1
- test issue HOT 1
- How to solve the problem that topK's K is different for every input text? HOT 1
- Dataset link HOT 1
- InvalidArgumentError: Default MaxPoolingOp only supports NHWC on device type CPU HOT 1
- how to reproduce the evaluation results
- link to dataset is broken
- what is your tensorflow version?
- Can't use model.predict_proba in function API
- loss function may be not right HOT 2
- Classify an Image independently HOT 7
- How to use the costomised data to train the model? HOT 6
- error occurred when I run the miml.ipnb HOT 1
- weight file HOT 1
- hello,you did excellent work,i studied your project of Multi-Label-Image-Classification,and i got some problem of the part process data,can you share me the code of processing data?Ths! HOT 12
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