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(>=2024.12.30)"] +plot = ["matplotlib"] +test = ["cmapfile", "czifile", "dask", "defusedxml", "fsspec", "imagecodecs", "lfdfiles", "lxml", "ndtiff", "oiffile", "psdtags", "pytest", "roifile", "xarray", "zarr (<3)"] +xml = ["defusedxml", "lxml"] +zarr = ["fsspec", "zarr (<3)"] + [[package]] name = "traitlets" version = "5.12.0" @@ -3148,4 +3629,4 @@ testing = ["coverage (>=5.0.3)", "zope.event", "zope.testing"] [metadata] lock-version = "2.0" python-versions = "^3.11" -content-hash = "3fad1a8073278577998125ec05cb516de5b4ed9973b4c267fe40d53854c1613b" +content-hash = "031b706da68ac6b9eacdb2c7febde1918019a91c79477dcff2fdd78d219d1fd5" diff --git a/server/portal/apps/_custom/drp/models.py b/server/portal/apps/_custom/drp/models.py index 999aa1434..095fe853c 100644 --- a/server/portal/apps/_custom/drp/models.py +++ b/server/portal/apps/_custom/drp/models.py @@ -41,6 +41,7 @@ class DrpFileMetadata(DrpMetadataModel): offset_to_first_image: Optional[int] = None gap_between_images: Optional[int] = None byte_order: Optional[Literal['big_endian', 'little_endian']] = None + use_binary_correction: Optional[bool] = None class FileObj(DrpMetadataModel): """Model for associated files""" diff --git a/server/portal/apps/projects/tasks.py b/server/portal/apps/projects/tasks.py index f36703dc2..79a7d6b3b 100644 --- a/server/portal/apps/projects/tasks.py +++ b/server/portal/apps/projects/tasks.py @@ -1,19 +1,34 @@ +import os +import base64 import logging from pathlib import Path from django.conf import settings from celery import shared_task from django.db import transaction from portal.apps.publications.models import PublicationRequest -from portal.apps import SCHEMA_MAPPING from portal.libs.agave.utils import user_account, service_account from django.contrib.auth import get_user_model from django.core.exceptions import ObjectDoesNotExist from portal.apps.projects.models.project_metadata import ProjectMetadata from portal.apps._custom.drp import constants -from portal.apps.projects.workspace_operations.project_meta_operations import add_file_associations, create_file_obj, get_ordered_value +from portal.apps.projects.workspace_operations.project_meta_operations import ( + add_file_associations, + create_file_obj, + get_file_obj, + get_ordered_value + ) from portal.apps.projects.workspace_operations.graph_operations import get_path_uuid_mapping import networkx as nx -import uuid +from portal.apps._custom.drp.models import FileObj +from portal.libs.files.file_processing import ( + binary_correction, + conf_raw, + conf_tiff, + create_animation, + create_histogram, + create_thumbnail + ) +from portal.apps.notifications.models import Notification # TODO: Cleanup this file @@ -231,4 +246,91 @@ def sync_files_without_metadata(self, user_access_token, project_id: str): for entity_uuid, file_objs in files_to_add_dict.items(): logger.info(f'Adding {len(file_objs)} files to entity {entity_uuid} in project {project_id}') add_file_associations(entity_uuid, file_objs) - \ No newline at end of file + +@shared_task(bind=True, queue='default') +def process_file(self, project_id: str, path: str, user_access_token: str, encoded_file=None): + + client = user_account(user_access_token) + username = client.access_token.claims['tapis/username'] + + Notification.objects.create(**{ + Notification.EVENT_TYPE: 'default', + Notification.STATUS: Notification.INFO, + Notification.USER: username, + Notification.MESSAGE: f'Generating Images', + }) + + logger.info(f'Processing file {path} in project {project_id}') + + if encoded_file: + logger.info('Decoding file') + file = base64.b64decode(encoded_file) + else: + logger.info('Retrieving file using Tapis') + file = client.files.getContents(systemId=project_id, path=path) + + logger.info('File retrieved') + + parent_path = str(Path(path).parent) + + file_obj: FileObj = get_file_obj(project_id, path) + + if file and file_obj: + value = get_ordered_value(constants.FILE, file_obj.get('value')) + + file_name = file_obj.get('name') + + _, file_ext = os.path.splitext(file_obj.get('name')) + + if file_ext in ['.tif', '.tiff']: + adv_image = conf_tiff(file) + else: + adv_image = conf_raw(value, file) + + try: + if value.get('use_binary_correction'): + adv_image = binary_correction(adv_image) + except Exception as e: + logger.error(f'Error applying binary correction: {e}') + + try: + thumbnail = create_thumbnail(adv_image) + + thumbnail_path = f'{parent_path}/{file_name}.thumb.jpg' + + logger.info('Uploading generated thumbnail') + client.files.insert(systemId=project_id, path=thumbnail_path, file=thumbnail) + except Exception as e: + logger.error(f'Error generating thumbnail: {e}') + + try: + histogram_img, histogram_csv = create_histogram(adv_image) + + histogram_img_path = f'{parent_path}/{file_name}.histogram.jpg' + histogram_csv_path = f'{parent_path}/{file_name}.histogram.csv' + + logger.info('Uploading generated histogram') + client.files.insert(systemId=project_id, path=histogram_img_path, file=histogram_img) + client.files.insert(systemId=project_id, path=histogram_csv_path, file=histogram_csv) + except Exception as e: + logger.error(f'Error generating histogram: {e}') + + try: + animation = create_animation(adv_image) + + animation_path = f'{parent_path}/{file_name}.gif' + + logger.info('Uploading generated animation') + client.files.insert(systemId=project_id, path=animation_path, file=animation) + except Exception as e: + logger.error(f'Error generating animation: {e}') + + with transaction.atomic(): + Notification.objects.create(**{ + Notification.EVENT_TYPE: 'default', + Notification.STATUS: Notification.INFO, + Notification.USER: username, + Notification.MESSAGE: f'Image generation complete. Please refresh the page.', + }) + else: + print(f"File {path} does not exist in project {project_id}") diff --git a/server/portal/apps/projects/views.py b/server/portal/apps/projects/views.py index e5b6246c1..8350cdcd3 100644 --- a/server/portal/apps/projects/views.py +++ b/server/portal/apps/projects/views.py @@ -33,7 +33,7 @@ from pathlib import Path from portal.apps._custom.drp import constants from portal.apps.projects.workspace_operations.graph_operations import add_node_to_project, initialize_project_graph, get_node_from_path -from portal.apps.projects.tasks import sync_files_without_metadata +from portal.apps.projects.tasks import process_file, sync_files_without_metadata LOGGER = logging.getLogger(__name__) @@ -398,6 +398,7 @@ def patch(self, request: HttpRequest, project_id: str): if value['data_type'] == 'file': try: patch_file_obj_entity(client, project_id, value, path) + process_file.delay(project_id, path.lstrip("/"), client.access_token.access_token) except Exception as exc: raise ApiException("Error updating file metadata", status=500) from exc else: diff --git a/server/portal/libs/agave/operations.py b/server/portal/libs/agave/operations.py index 761f63dbe..66129947f 100644 --- a/server/portal/libs/agave/operations.py +++ b/server/portal/libs/agave/operations.py @@ -1,3 +1,4 @@ +import base64 import os import io from django.conf import settings @@ -11,6 +12,7 @@ from portal.libs.agave.filter_mapping import filter_mapping from pathlib import Path from portal.apps._custom.drp.models import FileObj +from portal.apps.projects.tasks import process_file from tapipy.errors import BaseTapyException from portal.apps.projects.models.metadata import ProjectsMetadata from portal.apps.datafiles.models import DataFilesMetadata @@ -558,6 +560,11 @@ def upload(client, system, path, uploaded_file, metadata=None): root_node = get_root_node(system) add_file_associations(root_node['uuid'], [file_obj]) + # additional processing for files + encoded_file = base64.b64encode(uploaded_file.read()).decode('utf-8') + uploaded_file.seek(0) + transaction.on_commit(lambda: process_file.delay(file_obj.system, file_obj.path, client.access_token.access_token, encoded_file)) + response_json = client.files.insert(systemId=system, path=dest_path, file=uploaded_file) tapis_indexer.apply_async(kwargs={'access_token': client.access_token.access_token, 'systemId': system, diff --git a/server/portal/libs/files/file_processing.py b/server/portal/libs/files/file_processing.py new file mode 100644 index 000000000..c86e128ec --- /dev/null +++ b/server/portal/libs/files/file_processing.py @@ -0,0 +1,183 @@ +import numpy as np +import io +import logging +from matplotlib import pyplot as plt +import csv +import matplotlib.animation as anim +import tempfile +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 \ No newline at end of file diff --git a/server/pyproject.toml b/server/pyproject.toml index b7163c531..3944c5e4d 100644 --- a/server/pyproject.toml +++ b/server/pyproject.toml @@ -41,6 +41,9 @@ gevent = "^23.9.1" pymemcache = "^4.0.0" pydantic = "^2.5.0" networkx = "^3.2.1" +numpy = "^2.2.1" +matplotlib = "^3.10.0" +tifffile = "^2025.1.10" [tool.poetry.group.dev.dependencies] pytest = "^7.3.1"