-
Notifications
You must be signed in to change notification settings - Fork 0
Commit
This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository.
Added image processing for files with metadata
- Image processing runs on upload and whenever the metadata is updated
- Loading branch information
1 parent
ae6dffa
commit 7ce9c51
Showing
7 changed files
with
757 additions
and
5 deletions.
There are no files selected for viewing
Large diffs are not rendered by default.
Oops, something went wrong.
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,184 @@ | ||
| import numpy as np | ||
| import io | ||
| import logging | ||
| from matplotlib import pyplot as plt | ||
| import csv | ||
| import matplotlib.animation as anim | ||
| import tempfile | ||
| from portal.apps._custom.drp.models import DrpFileMetadata, FileObj | ||
| import tifffile as tiff | ||
|
|
||
| logger = logging.getLogger(__name__) | ||
|
|
||
| def conf_raw(img, file): | ||
| # NOTE: As mentioned above, this datatype should be an auto generated field | ||
| # in the adv image upload form for RAW files. The image parameters for | ||
| # slices, width, height should be converted to ints | ||
| # NOTE: If an 8-bit raw comes through, we need to set the datatype for that to unsigned. | ||
|
|
||
| logger.info(f'img: {img}') | ||
|
|
||
| prefix_map = {'little_endian': '<', 'big_endian': '>'} | ||
| suffix_map = { | ||
| '8_bit': 'u1', '16_bit_unsigned': 'u2', '32_bit_unsigned': 'u4', '64_bit_unsigned': 'u8', | ||
| '8_bit_signed': 'i1', '16_bit_signed': 'i2', '32_bit_signed': 'i4', '64_bit_signed': 'i8', | ||
| '32_bit_real': 'f4', '64_bit_real': 'f8' | ||
| } | ||
|
|
||
| prefix = prefix_map.get(img['byte_order'], '|') # Default to native byte order if unknown | ||
| suffix = suffix_map.get(img['image_type']) | ||
| datatype = prefix + suffix | ||
|
|
||
| file_data = np.frombuffer(file, dtype=datatype) | ||
| return file_data.reshape([ | ||
| int(img['number_of_images']), | ||
| int(img['height']), | ||
| int(img['width']) | ||
| ]) | ||
|
|
||
| def conf_tiff(file): | ||
| with io.BytesIO(file) as buffer: | ||
| image = tiff.imread(buffer) | ||
| return image | ||
|
|
||
| def binary_correction(img): | ||
| logger.debug('Correcting for Binary values...') | ||
| min_value = np.min(img) | ||
| max_value = np.max(img) | ||
| k=255/(max_value-min_value) | ||
| l=-k*min_value | ||
|
|
||
| image1=np.floor(img * k + l) | ||
| del img | ||
| return image1.astype('uint8') | ||
|
|
||
| def create_thumbnail(img): | ||
| dpi = 100 | ||
| dim_max = 5 | ||
| width = img.shape[1] | ||
| height = img.shape[0] | ||
| depth_slice = None | ||
| if len(img.shape) == 3 and 3 not in img.shape: | ||
| width = img.shape[2] | ||
| height = img.shape[1] | ||
| depth_slice = int(np.ceil(img.shape[0]/2)) | ||
| elif len(img.shape) == 3 and 3 in img.shape: | ||
| # TODO: Handle RGB files shape ==> (h, w, 3) | ||
| logger.debug('handle RGB') | ||
|
|
||
| # preserve aspect ratio and resize to fit. | ||
| modifier = dim_max/width if width>height else dim_max/height | ||
| resized_width = width*modifier | ||
| resized_height = height*modifier | ||
|
|
||
| fig = plt.figure() | ||
| fig.set_size_inches(resized_width, resized_height, dpi) | ||
| ax = plt.Axes(fig, [0., 0., 1., 1.]) | ||
| ax.set_axis_off() | ||
| fig.add_axes(ax) | ||
| # TODO: Swap color mapping if image is bitmap/8bit | ||
| # plt.set_cmap('gray') if img.invert_colors else plt.set_cmap('Greys') | ||
| plt.set_cmap('Greys') | ||
| if depth_slice: | ||
| logger.debug('Creating Thumbnail from 3D tif') | ||
| ax.imshow(img[depth_slice,:,:], aspect='equal', vmin=0, vmax=255) | ||
| else: | ||
| logger.debug('Creating Thumbnail from FLAT tif') | ||
| ax.imshow(img, aspect='equal') | ||
|
|
||
| buffer = io.BytesIO() | ||
| plt.savefig(buffer, format='jpeg', dpi=dpi) | ||
| buffer.seek(0) | ||
|
|
||
| plt.close(fig) | ||
|
|
||
| return buffer.getvalue() | ||
|
|
||
| def create_histogram(img): | ||
| logger.debug('Creating Histogram') | ||
| nbins=256 | ||
| fig_hist = plt.figure(figsize=(4,2.4)) | ||
| freq, bins, patches = plt.hist(img.reshape([np.size(img),]), nbins, density=True) | ||
| plt.xlabel('Gray value') | ||
| plt.ylabel('Probability') | ||
| plt.tight_layout() | ||
|
|
||
| image_buffer = io.BytesIO() | ||
| fig_hist.savefig(image_buffer, format='jpeg', dpi=200) | ||
| image_buffer.seek(0) | ||
| plt.close(fig_hist) | ||
|
|
||
| csv_buffer = io.StringIO() | ||
| histwriter = csv.writer(csv_buffer,delimiter=',') | ||
| histwriter.writerow(('Value','Probability')) | ||
| for i in range(np.size(freq)): | ||
| histwriter.writerow((bins[i],freq[i])) | ||
| csv_buffer.seek(0) | ||
|
|
||
| logger.debug('Histogram Created') | ||
|
|
||
| return image_buffer.getvalue(), csv_buffer.getvalue() | ||
|
|
||
| def create_animation(img): | ||
| """ | ||
| Creates an animated GIF in memory using matplotlib and returns its binary data. | ||
| Args: | ||
| img (ndarray): The input 3D image as a NumPy array. | ||
| Returns: | ||
| bytes: Binary data of the animated GIF. | ||
| """ | ||
| if len(img.shape) < 3 or (len(img.shape) == 3 and 3 in img.shape): | ||
| logger.debug('Image is not a 3D array') | ||
| return # Exit if the image is not a 3D array | ||
|
|
||
| logger.debug('Creating Animated Gif') | ||
|
|
||
| class AnimatedGif: | ||
| def __init__(self): | ||
| self.fig = plt.figure() | ||
| self.images = [] | ||
|
|
||
| def add(self, image, h, w, dpi=100): | ||
| self.fig.set_size_inches(w, h, dpi) | ||
| ax1 = plt.Axes(self.fig, [0., 0., 1., 1.]) | ||
| ax1.set_axis_off() | ||
| self.fig.add_axes(ax1) | ||
| plt.set_cmap('Greys') | ||
| plt_im = ax1.imshow(image, aspect='equal', vmin=0, vmax=255) | ||
| self.images.append([plt_im]) | ||
|
|
||
| def save_to_tempfile(self): | ||
| """Saves the animation to a temporary file and returns its binary content.""" | ||
| with tempfile.NamedTemporaryFile(suffix=".gif", delete=True) as temp_file: | ||
| animation = anim.ArtistAnimation(self.fig, self.images) | ||
| animation.save(temp_file.name, writer='imagemagick', fps=6) | ||
| temp_file.seek(0) # Reset pointer to the beginning | ||
| return temp_file.read() # Read binary content | ||
|
|
||
| # Resize the image while preserving aspect ratio | ||
| dim_max = 5 | ||
| width, height = img.shape[2], img.shape[1] | ||
| modifier = dim_max / width if width > height else dim_max / height | ||
| resized_width, resized_height = width * modifier, height * modifier | ||
|
|
||
| # Create the animation | ||
| sl1 = img[0, :, :] | ||
| animated_gif = AnimatedGif() | ||
| animated_gif.add(sl1, h=resized_height, w=resized_width) | ||
|
|
||
| if img.shape[0] < 100: | ||
| slicesave = 1 | ||
| else: | ||
| slicesave = round((img.shape[0] / 100) * 1) | ||
|
|
||
| for i in range(1, img.shape[0], slicesave): | ||
| sl = img[i, :, :] | ||
| animated_gif.add(sl, h=resized_height, w=resized_width) | ||
|
|
||
| # Save the animation to a temporary file and return its binary data | ||
| gif_binary_data = animated_gif.save_to_tempfile() | ||
|
|
||
| logger.debug('Animated Gif Created') | ||
| return gif_binary_data |
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters