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✨ Image Normalizer

Image Normalizer is a class that resizes, crops and normalizes images. Since normalization is highly dependent on the model, it is recommended to have it as part of the encoders instead of using it in a dedicated executor. Therefore, misconfigurations resulting in a training-serving-gap are less likely.

The following parameters can be used:

• resize_dim (int): The size of the image after resizing
• target_size (tuple or int): The dimensions to crop the image to (center cropping is used)
• img_mean (tuple, default (0,0,0)): The mean for normalization
• img_std (tuple, default (1,1,1)): The standard deviation for normalization
• channel_axis (int): The channel axis in the images used
• target_channel_axis (int): The desired channel axis in the images. If this is not equal to the channel_axis, the axis is moved.
• target_dtype (np.dtype, default np.float32): The desired type of the image array

Table of Contents

• 🌱 Prerequisites
• 🚀 Usages
• 🎉️ Example
• 🔍️ Reference

🌱 Prerequisites

No prerequisites are required to run this executor.

🚀 Usages

🚚 Via JinaHub

using docker images

Use the prebuilt images from JinaHub in your python codes,

from jina import Flow
	
f = Flow().add(uses='jinahub+docker://ImageNormalizer')

or in the .yml config.

jtype: Flow
pods:
  - name: encoder
    uses: 'jinahub+docker://ImageNormalizer'
    override_with: 
      target_size: 42

using source codes

Use the source codes from JinaHub in your python codes,

from jina import Flow
	
f = Flow().add(uses='jinahub://ImageNormalizer')

or in the .yml config.

jtype: Flow
pods:
  - name: encoder
    uses: 'jinahub://ImageNormalizer'

📦️ Via Pypi

1. Install the executor-image-normalizer package.

   pip install git+https://github.com/jina-ai/executor-image-normalizer.git

2. Use executor-image-normalizer in your code

   from jina import Flow
   from jinahub.image.normalizer import ImageNormalizer
   
   f = Flow().add(uses=ImageNormalizer)

🐳 Via Docker

1. Clone the repo and build the docker image

   git clone https://github.com/jina-ai/executor-image-normalizer.git
   cd executor-image-normalizer
   docker build -t image-normalizer .

2. Use image-normalizer in your codes

   from jina import Flow
   
   f = Flow().add(uses='docker://image-normalizer')

🎉️ Example

from jina import Flow, Document

f = Flow().add(uses='jinahub+docker://ImageNormalizer')

with f:
    resp = f.post(on='foo', inputs=Document(), return_results=True)
    print(f'{resp}')

Inputs

Document with image blob.

Returns

Document with overridden image blob that is normalized, scaled, cropped and resized as instructed.

🔍️ Reference