Convert numpy array to image without loading it into RAM.

[paul18fr]

Some time ago, I used h5py to record pictures into a h5 file (very usefull and powerfull); in the following example:

1. a basic image is created using matplotlib
   
2. the image is saved into the h5 file as a picture (you can see it under hdfview for instance)
   
3. the image is saved into the h5 file as an array
   
4. the previous picture is recovered an saved locally into a gif image
   

(you can create a gif animated with ImageMagick for instance, but it's another topic)

Here after 2 screenshots of the picture into hdfview.

Maybe it add some features on your project.

Paul

import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvas
import os, h5py
 
Path = str(os.getcwd())

### 0) to create a fig
plt.style.use('_mpl-gallery')

# make data
x = np.linspace(0, 10, 100)
y = 4 + 2 * np.sin(2 * x)

# plot
fig, ax = plt.subplots(figsize=(16,16))
ax.plot(x, y, linewidth=2.0)

ax.set(xlim=(0, 8), xticks=np.arange(1, 8),
       ylim=(0, 8), yticks=np.arange(1, 8))

plt.show()
 
 
## 1) Convertion  Matplotlib fig into aNumpyArray ---> mandatory to change the picture into a matrix      
canvas = FigureCanvas(fig)
canvas.draw()
FigArray = np.array(canvas.renderer.buffer_rgba())
 
## 2) write directly a picture into the h5 file --> Note dataset is MANDATORY
h5 = h5py.File(Path + '/test_picture.h5', 'w')
ImageDataset = h5.create_dataset(name = "Example_picture", data = FigArray, dtype = 'uint8', compression = 'gzip')
ImageDataset.attrs["CLASS"] = np.string_("IMAGE")
ImageDataset.attrs["IMAGE_VERSION"] = np.string_("1.2")
ImageDataset.attrs["IMAGE_SUBCLASS"] = np.string_("IMAGE_TRUECOLOR")
ImageDataset.attrs["INTERLACE_MODE"] = np.string_("INTERLACE_MODE")
ImageDataset.attrs["IMAGE_MINMAXRANGE"] = np.uint8(0.255)
h5.close()


## 3) Write the fig into a basic array (the h5 file)
h5 = h5py.File(Path + '/test_array.h5', 'w')
NpArrays = h5.create_group('Fig')
DatasetFigs = NpArrays.create_dataset(name = 'Example of array', data = FigArray, dtype='f', compression = 'gzip')
h5.flush()
h5.close()


## 4) array recovering => save into a gif file
from PIL import Image as im
with h5py.File(Path + '/test_picture.h5','r') as pict:
    data = pict.get('/Example_picture')
    Array = np.array(data)
    
    # array is converted int a picture
    Picture = im.fromarray(Array)
    Picture.save(Path + '/export.gif')