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128 lines
4.2 KiB
Markdown
128 lines
4.2 KiB
Markdown
# Autoquality
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imgproxy can calculate quality for your resultant images so they best fit the selected metric. The supported methods are [none](#none), [size](#autoquality-by-file-size), [dssim](#autoquality-by-dssim), and [ml](#autoquality-with-ml).
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**⚠️ Warning:** Autoquality requires an image to be saved several times. Use it only when you prefer the resultant quality and size over speed.
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You can enable autoquality using [config options](configuration.md#autoquality) (for all images) or with [processing options](generating_the_url.md#autoquality) (for each image individually).
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## None
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Disable the autoquality.
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**Method name:** `none`
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#### Config example
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```bash
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IMGPROXY_AUTOQUALITY_METHOD="none"
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```
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#### Processing options example
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```
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.../autoquality:none/...
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```
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## Autoquality by file size
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With this method, imgproxy will try to degrade the quality so your image fits the desired file size.
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**Method name:** `size`
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**Target:** the desired file size
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#### Config example
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```bash
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IMGPROXY_AUTOQUALITY_METHOD="size"
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# Change value to the desired size in bytes
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IMGPROXY_AUTOQUALITY_TARGET=10240
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IMGPROXY_AUTOQUALITY_MIN=10
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IMGPROXY_AUTOQUALITY_MAX=80
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# Quality 50 for AVIF is pretty the same as 80 for JPEG
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IMGPROXY_AUTOQUALITY_FORMAT_MAX="avif=50"
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```
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#### Processing options example
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```
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.../autoquality:size:10240:10:80/...
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```
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## Autoquality by DSSIM
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With this method imgproxy will try to select a level of quality so that the saved image will have the desired [DSSIM](https://en.wikipedia.org/wiki/Structural_similarity#Structural_Dissimilarity) value.
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**Method name:** `dssim`
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**Target:** the desired DSSIM value
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#### Config example
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```bash
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IMGPROXY_AUTOQUALITY_METHOD="dssim"
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# Change value to the desired DSSIM
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IMGPROXY_AUTOQUALITY_TARGET=0.02
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# We're happy enough if the resulting DSSIM will differ from the desired by 0.001
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IMGPROXY_AUTOQUALITY_ALLOWED_ERROR=0.001
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IMGPROXY_AUTOQUALITY_MIN=70
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IMGPROXY_AUTOQUALITY_MAX=80
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# Quality 50 for AVIF is pretty the same as 80 for JPEG
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IMGPROXY_AUTOQUALITY_FORMAT_MIN="avif=40"
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IMGPROXY_AUTOQUALITY_FORMAT_MAX="avif=50"
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```
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#### Processing options example
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```
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.../autoquality:dssim:0.02:70:80:0.001/...
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```
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## Autoquality with ML
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This method is almost the same as autoquality with [DSSIM](#autoquality-by-dssim) but imgproxy will try to predict the initial quality using neural networks. This requires neural networks to be configured (see the config examlpe or the config documentation). If a neural network for the resulting format is not provided, the [DSSIM](#autoquality-by-dssim) method will be used instead.
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**📝 Note:** When this method is used, imgproxy will save JPEG images with the most optimal [advanced JPEG compression](configuration.md#advanced-jpeg-compression) settings, ignoring config and processing options.
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**Method name:** `ml`
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**Target:** the desired DSSIM value
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#### Config example
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```bash
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IMGPROXY_AUTOQUALITY_METHOD="ml"
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# Change value to the desired DSSIM
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IMGPROXY_AUTOQUALITY_TARGET=0.02
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# We're happy enough if the resulting DSSIM will differ from the desired by 0.001
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IMGPROXY_AUTOQUALITY_ALLOWED_ERROR=0.001
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IMGPROXY_AUTOQUALITY_MIN=70
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IMGPROXY_AUTOQUALITY_MAX=80
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# Quality 50 for AVIF is pretty the same as 80 for JPEG
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IMGPROXY_AUTOQUALITY_FORMAT_MIN="avif=40"
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IMGPROXY_AUTOQUALITY_FORMAT_MAX="avif=50"
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# Neural networks paths for JPEG, WebP, and AVIF
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IMGPROXY_AUTOQUALITY_JPEG_NET="/networks/autoquality-jpeg.pb"
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IMGPROXY_AUTOQUALITY_WEBP_NET="/networks/autoquality-webp.pb"
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IMGPROXY_AUTOQUALITY_AVIF_NET="/networks/autoquality-avif.pb"
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```
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**📝 Note:** If you trust your neural network's autoquality, you may want to set `IMGPROXY_AUTOQUALITY_ALLOWED_ERROR` to 1 (the maximum possible DSSIM value). In this case, imgproxy will always use the quality predicted by the neural network.
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#### Processing options example
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```
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.../autoquality:ml:0.02:70:80:0.001/...
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```
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### Neural networks format
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Neural networks should fit the following requirements:
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* Tensorflow frozen graph format
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* Input layer size is 416x416
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* Output layer size is 1x100
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* Output layer values are logits of quality probabilities
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If you're an imgproxy Pro user and you want to train your own network but you don't know how, feel free to contact the imgproxy team for instructions.
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