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Keras 教學 - 透過預先訓練神經網路特徵萃取法快速訓練高準確度模型
Keras 教學 – 透過預先訓練神經網路特徵萃取法快速訓練高準確度模型
預先訓練神經網路的特徵萃取法 我們知道 CNN 卷積層的訓練需要很多數據與運算資源，在資料集不足的情況下，從頭訓練卷積層不是一個聰明的方法。何不直接採用大神訓練好的卷積層，加速 AI Time to Market。這樣的方法稱為預先訓練神經網路的特徵萃取法 (Feature extraction with a pertrained network)，由於在 CNN 架構中訓練 Convolutional Layer 成本是很高的，太少的樣本不足以訓練出具有特徵擷取意義的網路。Convolutional Layer 如下： Convolutional 主要用來擷取特徵，在不同的業務需求下，前端對於影響的特徵擷取其實是可以共用的。所以我們想站在巨人的肩膀上，直接使用一些典型網路已經訓練好的 Convolutional Base 來擷取特徵，透過特徵重新訓練自己的 Full…
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After many many hours of training and debugging I have FINALLY completed with 100% working conditions the first step in NVIDIA’s styleGAN2 architecture with networks trained on cartoons. While the model is only 85% accurate, I can give it a query image and it will guess correctly. Opposed to just guessing the same pokemon for every single image.
If I ever need to question how to access the dictionary that Imagedatagenerator returns it is here
It may be incorrect but through many errors I can query a single image at the end of the runtime. So, time to simply increase accuracy and get better results
Next quarter I might want to explore different pipelines for creating data set feeding. Here they claim my process is slow and not as tunable. but I think it will suffice
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VGG Testing Update
I believe that I have tuned it about 90% of they way I need to. My loss isn’t perfect still. Given that this methodology, architecture, works for others, I think these parameters work best on my system. Now I need to test it against images it has never seen, then deploy
Testing VGG
Before I scrape through google images and abuse Bing API I tested the VGG16 on a cat and dog dataset. The image shows my progress. I am encouraged by everything except my validation loss, it hardly follows the training loss so I will have to tweak some parameters to get better performance from my AI. Nonetheless, ending around 90% accuracy is still nice I guess.
Since ImageDataGenerator() makes it easy to classify images based on your directory, I am going to create an Image directory as depicted. I might add more specific classes but for the sake of my project for now, it isn’t needed.
