diff --git a/.dockerignore b/.dockerignore
new file mode 100644
index 00000000..7257b442
--- /dev/null
+++ b/.dockerignore
@@ -0,0 +1,11 @@
+dist
+build
+igneous.egg-info
+*.so
+.eggs
+*.pyc
+__pycache__
+.cache
+test.py
+pipeline.py
+.pytest_cache
diff --git a/.travis.yml b/.travis.yml
index ced20e45..22eb2ab5 100755
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,8 +1,5 @@
language: python
python:
-- '2.7'
-- '3.4'
-- '3.5'
- '3.6'
dist: trusty
sudo: required
@@ -13,12 +10,12 @@ before_install:
- sudo mv secrets /secrets && sudo chown $USER /secrets
- sudo mkdir -p $HOME/.cloudvolume
- sudo ln -s /secrets $HOME/.cloudvolume/secrets
-- $(python version.py)
+- $(python igneous_version.py)
script:
- docker build --tag seunglab/igneous:$APPVERSION . || travis_terminate 1
- docker run -it -v /secrets:/secrets seunglab/igneous:$APPVERSION /bin/sh -c "cd /igneous
&& py.test -v -x test" || travis_terminate 1;
-- docker login -u="$DOCKER_USERNAME" -p="$DOCKER_PASSWORD" || travis_terminate 1;
+- echo "$DOCKER_PASSWORD" | docker login -u="$DOCKER_USERNAME" --password-stdin || travis_terminate 1;
- if [ "$TRAVIS_BRANCH" == "master" ];
then
docker push seunglab/igneous || travis_terminate 1;
diff --git a/Dockerfile b/Dockerfile
index d44696d3..6d68ee30 100755
--- a/Dockerfile
+++ b/Dockerfile
@@ -1,48 +1,32 @@
-FROM python:3.4
-MAINTAINER William Silversmith
-# This image contains private keys, make sure the image is not pushed to docker hub or any public repo.
-## INSTALL gsutil
-# Prepare the image.
-ENV DEBIAN_FRONTEND noninteractive
-RUN apt-get update && apt-get install -y -qq --no-install-recommends \
- apt-utils \
- curl \
- git \
- openssh-client \
- python-openssl \
- python \
- python-pip \
- python-dev \
-# python-h5py \
- python-numpy \
- python-setuptools \
- libboost-all-dev \
-# libhdf5-dev \
- liblzma-dev \
- libgmp-dev \
-# libmpfr-dev \
-# libxml2-dev \
- screen \
- software-properties-common \
- unzip \
- vim \
- wget \
- zlib1g-dev \
- && apt-get clean \
- && rm -rf /var/lib/apt/lists/*
-
-RUN pip install setuptools Cython wheel numpy
+FROM python:3.6-slim
+LABEL maintainer="William Silversmith, Nico Kemnitz"
-# install neuroglancer
-RUN mkdir /.ssh
ADD ./ /igneous
-RUN pip install -r /igneous/requirements.txt
-RUN pip install pyasn1 --upgrade
-RUN cd /igneous && pip install -e .
+RUN apt-get update \
+ # Build dependencies
+ && apt-get install -y -qq --no-install-recommends \
+ git \
+ libboost-dev \
+ build-essential \
+ # igneous + runtime dependencies
+ && cd igneous \
+ && pip install --no-cache-dir -r requirements.txt \
+ && pip install --no-cache-dir -e . \
+ \
+ # Cleanup build dependencies
+ && apt-get remove --purge -y \
+ libboost-dev \
+ build-essential \
+ && apt-get autoremove --purge -y \
+ # Cleanup apt
+ && apt-get clean \
+ && rm -rf /var/lib/apt/lists/* \
+ # Cleanup temporary python files
+ && find /usr/local/lib/python3.6 -depth \
+ \( \
+ \( -type d -a \( -name __pycache__ \) \) \
+ -o \
+ \( -type f -a \( -name '*.pyc' -o -name '*.pyo' \) \) \
+ \) -exec rm -rf '{}' +
CMD python /igneous/igneous/task_execution.py
-
-
-
-
-
diff --git a/LICENSE b/LICENSE
new file mode 100644
index 00000000..f288702d
--- /dev/null
+++ b/LICENSE
@@ -0,0 +1,674 @@
+ GNU GENERAL PUBLIC LICENSE
+ Version 3, 29 June 2007
+
+ Copyright (C) 2007 Free Software Foundation, Inc.
+ Everyone is permitted to copy and distribute verbatim copies
+ of this license document, but changing it is not allowed.
+
+ Preamble
+
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+software and other kinds of works.
+
+ The licenses for most software and other practical works are designed
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+the GNU General Public License is intended to guarantee your freedom to
+share and change all versions of a program--to make sure it remains free
+software for all its users. We, the Free Software Foundation, use the
+GNU General Public License for most of our software; it applies also to
+any other work released this way by its authors. You can apply it to
+your programs, too.
+
+ When we speak of free software, we are referring to freedom, not
+price. Our General Public Licenses are designed to make sure that you
+have the freedom to distribute copies of free software (and charge for
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+
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+these rights or asking you to surrender the rights. Therefore, you have
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+you modify it: responsibilities to respect the freedom of others.
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+or that patent license was granted, prior to 28 March 2007.
+
+ Nothing in this License shall be construed as excluding or limiting
+any implied license or other defenses to infringement that may
+otherwise be available to you under applicable patent law.
+
+ 12. No Surrender of Others' Freedom.
+
+ If conditions are imposed on you (whether by court order, agreement or
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+
+ 13. Use with the GNU Affero General Public License.
+
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+
+ 14. Revised Versions of this License.
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+ The Free Software Foundation may publish revised and/or new versions of
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+address new problems or concerns.
+
+ Each version is given a distinguishing version number. If the
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+Foundation. If the Program does not specify a version number of the
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+
+ If the Program specifies that a proxy can decide which future
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+to choose that version for the Program.
+
+ Later license versions may give you additional or different
+permissions. However, no additional obligations are imposed on any
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+ 15. Disclaimer of Warranty.
+
+ THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
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+ 17. Interpretation of Sections 15 and 16.
+
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+Program, unless a warranty or assumption of liability accompanies a
+copy of the Program in return for a fee.
+
+ END OF TERMS AND CONDITIONS
+
+ How to Apply These Terms to Your New Programs
+
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+possible use to the public, the best way to achieve this is to make it
+free software which everyone can redistribute and change under these terms.
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+to attach them to the start of each source file to most effectively
+state the exclusion of warranty; and each file should have at least
+the "copyright" line and a pointer to where the full notice is found.
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+ Copyright (C)
+
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+ it under the terms of the GNU General Public License as published by
+ the Free Software Foundation, either version 3 of the License, or
+ (at your option) any later version.
+
+ This program is distributed in the hope that it will be useful,
+ but WITHOUT ANY WARRANTY; without even the implied warranty of
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+
+ You should have received a copy of the GNU General Public License
+ along with this program. If not, see .
+
+Also add information on how to contact you by electronic and paper mail.
+
+ If the program does terminal interaction, make it output a short
+notice like this when it starts in an interactive mode:
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+ Copyright (C)
+ This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
+ This is free software, and you are welcome to redistribute it
+ under certain conditions; type `show c' for details.
+
+The hypothetical commands `show w' and `show c' should show the appropriate
+parts of the General Public License. Of course, your program's commands
+might be different; for a GUI interface, you would use an "about box".
+
+ You should also get your employer (if you work as a programmer) or school,
+if any, to sign a "copyright disclaimer" for the program, if necessary.
+For more information on this, and how to apply and follow the GNU GPL, see
+.
+
+ The GNU General Public License does not permit incorporating your program
+into proprietary programs. If your program is a subroutine library, you
+may consider it more useful to permit linking proprietary applications with
+the library. If this is what you want to do, use the GNU Lesser General
+Public License instead of this License. But first, please read
+.
diff --git a/README.md b/README.md
index aada32c7..440cfd6c 100755
--- a/README.md
+++ b/README.md
@@ -1,4 +1,4 @@
-[![Build Status](https://travis-ci.org/seung-lab/igneous.svg?branch=master)](https://travis-ci.org/seung-lab/igneous)
+[![Build Status](https://travis-ci.org/seung-lab/igneous.svg?branch=master)](https://travis-ci.org/seung-lab/igneous) [![SfN 2018 Poster](https://img.shields.io/badge/poster-SfN%202018-blue.svg)](https://drive.google.com/open?id=1RKtaAGV2f7F13opnkQfbp6YBqmoD3fZi)
# Igneous
@@ -19,7 +19,9 @@ git clone git@github.com:seung-lab/igneous.git
cd igneous
virtualenv venv
source venv/bin/activate
-pip install -e .
+pip install numpy
+pip install -r requirements.txt
+python setup.py develop
```
The installation will download the dependencies listed in requirements.txt and
diff --git a/deployment.yaml b/deployment.yaml
index beca4367..4ca3fb0e 100755
--- a/deployment.yaml
+++ b/deployment.yaml
@@ -23,6 +23,8 @@ spec:
resources:
requests:
memory: 2.5Gi
+ limits:
+ memory: 7.0Gi
env:
- name: QUEUE_TYPE
value: aws
diff --git a/docker/chunkflow/Dockerfile b/docker/chunkflow/Dockerfile
index 1b236c87..00aa8a40 100755
--- a/docker/chunkflow/Dockerfile
+++ b/docker/chunkflow/Dockerfile
@@ -17,13 +17,13 @@ RUN apt-get update \
build-essential \
# igneous + runtime dependencies
&& cd igneous \
- && pip install --no-cache-dir -r requirements.txt \
+ && pip3 install --no-cache-dir -r requirements.txt \
# we can only use numpy==1.15 due to an issue of skimage:
# https://github.com/scikit-image/scikit-image/issues/3551
# the fix was not released yet.
# https://github.com/scikit-image/scikit-image/pull/3556
- && pip install numpy==1.15 --no-cache-dir \
- && pip install --no-cache-dir -e . \
+ && pip3 install numpy==1.15 --no-cache-dir \
+ && pip3 install --no-cache-dir -e . \
\
# Cleanup build dependencies
&& apt-get remove --purge -y \
@@ -34,7 +34,7 @@ RUN apt-get update \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/* \
# Cleanup temporary python files
- && find /usr/local/lib/python3.6 -depth \
+ && find /opt/conda/bin/python3.6 -depth \
\( \
\( -type d -a \( -name __pycache__ \) \) \
-o \
diff --git a/igneous/scripts/queue_pickle.py b/igneous/scripts/queue_pickle.py
index 1040591f..281e24f6 100755
--- a/igneous/scripts/queue_pickle.py
+++ b/igneous/scripts/queue_pickle.py
@@ -9,17 +9,29 @@
"""
from six.moves import range
+import copy
from datetime import datetime
import json
import math
import os
import click
+import numpy as np
from tqdm import tqdm
+from igneous import tasks
+from cloudvolume.lib import touch
from taskqueue import TaskQueue
+def serializenumpy(obj):
+ if isinstance(obj, np.ndarray):
+ return obj.tolist()
+ return obj
+
def deserialize(file):
+ if not os.path.exists(file):
+ return []
+
with open(file, 'r') as f:
queue = json.loads(f.read())
return queue
@@ -41,24 +53,43 @@ def save(qurl, file):
print("Restarting with {} as seed. Tasks: {}".format(file, len(queue)))
def save_progress(tq, last_few):
+ new_queue = [ ]
+
+ for obj in queue:
+ if type(obj) is dict:
+ task = obj
+ else:
+ task = copy.deepcopy(obj._args)
+ task['class'] = obj.__class__.__name__
+
+ new_queue.append(task)
+
+ def serializenumpy(obj):
+ if isinstance(obj, np.ndarray):
+ return obj.tolist()
+ return obj
+
with open(file, 'w') as f:
- f.write(json.dumps(queue))
+ f.write(json.dumps(new_queue, default=serializenumpy))
for t in last_few:
- tq.delete(t['id'])
+ tq.delete(t)
tq.wait()
# Get all task queues
- num_lease = 100
+ num_lease = 1
last_few = []
with TaskQueue(queue_server='sqs', qurl=qurl) as tq:
iters = int(math.ceil(float(tq.enqueued) / float(num_lease)))
for i in tqdm(range(iters), desc='Leasing Tasks'):
- tasks = tq.raw_lease(numTasks=num_lease, leaseSecs=10)
- queue.extend(tasks['items'])
- last_few.extend(tasks['items'])
+ tasks = tq.lease(num_tasks=num_lease, seconds=10)
+ if type(tasks) is not list:
+ tasks = [ tasks ]
+
+ queue.extend(tasks)
+ last_few.extend(tasks)
if i % 10 == 0:
save_progress(tq, last_few)
diff --git a/igneous/secrets.py b/igneous/secrets.py
index 5f807720..f3c318e6 100755
--- a/igneous/secrets.py
+++ b/igneous/secrets.py
@@ -16,7 +16,7 @@ def envval(key, default):
QUEUE_NAME = envval('PIPELINE_USER_QUEUE', 'pull-queue')
TEST_QUEUE_NAME = envval('TEST_PIPELINE_USER_QUEUE', 'test-pull-queue')
-QUEUE_TYPE = envval('QUEUE_TYPE', 'pull-queue')
+QUEUE_TYPE = envval('QUEUE_TYPE', 'sqs')
SQS_URL = envval('SQS_URL', None)
PROJECT_NAME = 'neuromancer-seung-import'
APPENGINE_QUEUE_URL = 'https://queue-dot-neuromancer-seung-import.appspot.com'
diff --git a/igneous/task_creation.py b/igneous/task_creation.py
index d234115c..bfb0b90d 100755
--- a/igneous/task_creation.py
+++ b/igneous/task_creation.py
@@ -3,19 +3,22 @@
from six.moves import range
from itertools import product
from functools import reduce
+import operator
import copy
import json
import math
import os
import re
+import subprocess
import time
from time import strftime
import numpy as np
from tqdm import tqdm
+import cloudvolume
from cloudvolume import CloudVolume, Storage
-from cloudvolume.lib import Vec, Bbox, max2, min2, xyzrange, find_closest_divisor
+from cloudvolume.lib import Vec, Bbox, max2, min2, xyzrange, find_closest_divisor, yellow
from taskqueue import TaskQueue, MockTaskQueue
from igneous import downsample_scales, chunks
@@ -28,7 +31,18 @@
)
# from igneous.tasks import BigArrayTask
-USER_EMAIL = 'ws9@princeton.edu' # for provenance files
+# for provenance files
+try:
+ OPERATOR_CONTACT = subprocess.check_output("git config user.email", shell=True)
+ OPERATOR_CONTACT = str(OPERATOR_CONTACT.rstrip())
+except:
+ try:
+ print(yellow('Unable to determine provenance contact email. Set "git config user.email". Using unix $USER instead.'))
+ OPERATOR_CONTACT = os.environ['USER']
+ except:
+ print(yellow('$USER was not set. The "owner" field of the provenance file will be blank.'))
+ OPERATOR_CONTACT = ''
+
def create_ingest_task(storage, task_queue):
"""
@@ -100,7 +114,11 @@ def create_info_file_from_build(layer_path, layer_type, resolution, encoding):
return vol.info
-def create_downsample_scales(layer_path, mip, ds_shape, axis='z', preserve_chunk_size=False):
+def create_downsample_scales(
+ layer_path, mip, ds_shape, axis='z',
+ preserve_chunk_size=False, chunk_size=None,
+ encoding=None
+ ):
vol = CloudVolume(layer_path, mip)
shape = min2(vol.volume_size, ds_shape)
@@ -109,6 +127,9 @@ def create_downsample_scales(layer_path, mip, ds_shape, axis='z', preserve_chunk
underlying_mip = (mip + 1) if (mip + 1) in vol.available_mips else mip
underlying_shape = vol.mip_underlying(underlying_mip).astype(np.float32)
+ if chunk_size:
+ underlying_shape = Vec(*chunk_size).astype(np.float32)
+
toidx = { 'x': 0, 'y': 1, 'z': 2 }
preserved_idx = toidx[axis]
underlying_shape[preserved_idx] = float('inf')
@@ -121,12 +142,25 @@ def create_downsample_scales(layer_path, mip, ds_shape, axis='z', preserve_chunk
scales = scales[1:] # omit (1,1,1)
scales = [ list(map(int, vol.downsample_ratio * Vec(*factor3))) for factor3 in scales ]
+ if len(scales) == 0:
+ print("WARNING: No scales generated.")
+
for scale in scales:
- vol.add_scale(scale)
+ vol.add_scale(scale, encoding=encoding, chunk_size=chunk_size)
- if preserve_chunk_size:
- for i in range(mip + 1, mip + len(scales) + 1):
- vol.scales[i]['chunk_sizes'] = vol.scales[mip]['chunk_sizes']
+ if chunk_size is None:
+ if preserve_chunk_size or len(scales) == 0:
+ chunk_size = vol.scales[mip]['chunk_sizes']
+ else:
+ chunk_size = vol.scales[mip + 1]['chunk_sizes']
+ else:
+ chunk_size = [ chunk_size ]
+
+ if encoding is None:
+ encoding = vol.scales[mip]['encoding']
+
+ for i in range(mip + 1, mip + len(scales) + 1):
+ vol.scales[i]['chunk_sizes'] = chunk_size
return vol.commit_info()
@@ -134,7 +168,8 @@ def create_downsampling_tasks(
task_queue, layer_path,
mip=0, fill_missing=False, axis='z',
num_mips=5, preserve_chunk_size=True,
- sparse=False, bounds=None
+ sparse=False, bounds=None, chunk_size=None,
+ encoding=None
):
"""
mip: Download this mip level, writes to mip levels greater than this one.
@@ -145,6 +180,7 @@ def create_downsampling_tasks(
preserve_chunk_size: if true, maintain chunk size of starting mip, else, find the closest
evenly divisible chunk size to 64,64,64 for this shape and use that. The latter can be
useful when mip 0 uses huge chunks and you want to simply visualize the upper mips.
+ chunk_size: (overrides preserve_chunk_size) force chunk size for new layers to be this.
sparse: When downsampling segmentation, if true, don't count black pixels when computing
the mode. Useful for e.g. synapses and point labels.
bounds: By default, downsample everything, but you can specify restricted bounding boxes
@@ -159,7 +195,11 @@ def ds_shape(mip):
vol = CloudVolume(layer_path, mip=mip)
shape = ds_shape(vol.mip)
- vol = create_downsample_scales(layer_path, mip, shape, preserve_chunk_size=preserve_chunk_size)
+ vol = create_downsample_scales(
+ layer_path, mip, shape,
+ preserve_chunk_size=preserve_chunk_size, chunk_size=chunk_size,
+ encoding=encoding
+ )
if not preserve_chunk_size:
shape = ds_shape(vol.mip + 1)
@@ -175,7 +215,8 @@ def ds_shape(mip):
print("Volume Bounds: ", vol.bounds)
print("Selected ROI: ", bounds)
- for startpt in tqdm(xyzrange( bounds.minpt, bounds.maxpt, shape ), desc="Inserting Downsample Tasks"):
+ total = reduce(operator.mul, np.ceil(bounds.size3() / shape))
+ for startpt in tqdm(xyzrange( bounds.minpt, bounds.maxpt, shape ), desc="Inserting Downsample Tasks", total=total):
task = DownsampleTask(
layer_path=layer_path,
mip=vol.mip,
@@ -186,6 +227,7 @@ def ds_shape(mip):
sparse=sparse,
)
task_queue.insert(task)
+
task_queue.wait('Uploading')
vol.provenance.processing.append({
'method': {
@@ -196,34 +238,61 @@ def ds_shape(mip):
'method': 'downsample_with_averaging' if vol.layer_type == 'image' else 'downsample_segmentation',
'sparse': sparse,
'bounds': str(bounds),
+ 'chunk_size': (list(chunk_size) if chunk_size else None),
+ 'preserve_chunk_size': preserve_chunk_size,
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
vol.commit_provenance()
-def create_deletion_tasks(task_queue, layer_path):
+def create_deletion_tasks(task_queue, layer_path, mip=0, num_mips=5):
vol = CloudVolume(layer_path)
- shape = vol.underlying * 10
+
+ shape = vol.mip_underlying(mip)[:3]
+ shape.x *= 2 ** num_mips
+ shape.y *= 2 ** num_mips
- for startpt in tqdm(xyzrange( vol.bounds.minpt, vol.bounds.maxpt, shape ), desc="Inserting Deletion Tasks"):
+ total_tasks = reduce(operator.mul, np.ceil(vol.bounds.size3() / shape))
+ for startpt in tqdm(xyzrange( vol.bounds.minpt, vol.bounds.maxpt, shape ), desc="Inserting Deletion Tasks", total=total_tasks):
bounded_shape = min2(shape, vol.bounds.maxpt - startpt)
task = DeleteTask(
layer_path=layer_path,
shape=bounded_shape.clone(),
offset=startpt.clone(),
+ mip=mip,
+ num_mips=num_mips,
)
task_queue.insert(task)
task_queue.wait('Uploading DeleteTasks')
-def create_meshing_tasks(task_queue, layer_path, mip, shape=Vec(512, 512, 512),
- max_simplification_error=40):
+ vol = CloudVolume(layer_path)
+ vol.provenance.processing.append({
+ 'method': {
+ 'task': 'DeleteTask',
+ 'mip': mip,
+ 'num_mips': num_mips,
+ 'shape': shape.tolist(),
+ },
+ 'by': OPERATOR_CONTACT,
+ 'date': strftime('%Y-%m-%d %H:%M %Z'),
+ })
+ vol.commit_provenance()
+
+def create_meshing_tasks(
+ task_queue, layer_path, mip,
+ shape=Vec(512, 512, 64), max_simplification_error=40,
+ mesh_dir=None, cdn_cache=False
+ ):
shape = Vec(*shape)
vol = CloudVolume(layer_path, mip)
+ if mesh_dir is None:
+ mesh_dir = 'mesh_mip_{}_err_{}'.format(mip, max_simplification_error)
+
if not 'mesh' in vol.info:
- vol.info['mesh'] = 'mesh_mip_{}_err_{}'.format(mip, max_simplification_error)
+ vol.info['mesh'] = mesh_dir
vol.commit_info()
for startpt in tqdm(xyzrange( vol.bounds.minpt, vol.bounds.maxpt, shape ), desc="Inserting Mesh Tasks"):
@@ -233,6 +302,8 @@ def create_meshing_tasks(task_queue, layer_path, mip, shape=Vec(512, 512, 512),
layer_path,
mip=vol.mip,
max_simplification_error=max_simplification_error,
+ mesh_dir=mesh_dir,
+ cache_control=('' if cdn_cache else 'no-cache'),
)
task_queue.insert(task)
task_queue.wait('Uploading MeshTasks')
@@ -242,9 +313,12 @@ def create_meshing_tasks(task_queue, layer_path, mip, shape=Vec(512, 512, 512),
'task': 'MeshTask',
'layer_path': layer_path,
'mip': vol.mip,
- 'shape': shape.tolist(),
+ 'shape': shape.tolist(),
+ 'max_simplification_error': max_simplification_error,
+ 'mesh_dir': mesh_dir,
+ 'cdn_cache': cdn_cache,
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
vol.commit_provenance()
@@ -252,32 +326,45 @@ def create_meshing_tasks(task_queue, layer_path, mip, shape=Vec(512, 512, 512),
def create_transfer_tasks(
task_queue, src_layer_path, dest_layer_path,
chunk_size=None, shape=Vec(2048, 2048, 64),
- fill_missing=False, translate=(0,0,0)
+ fill_missing=False, translate=(0,0,0),
+ bounds=None, mip=0, preserve_chunk_size=True
):
+ """
+ Transfer data from one data layer to another. It's possible
+ to transfer from a lower resolution mip level within a given
+ bounding box. The bounding box should be specified in terms of
+ the highest resolution.
+ """
shape = Vec(*shape)
- translate = Vec(*translate)
- vol = CloudVolume(src_layer_path)
+ vol = CloudVolume(src_layer_path, mip=mip)
+ translate = Vec(*translate) // vol.downsample_ratio
if not chunk_size:
- chunk_size = vol.info['scales'][0]['chunk_sizes'][0]
+ chunk_size = vol.info['scales'][mip]['chunk_sizes'][0]
chunk_size = Vec(*chunk_size)
try:
- dvol = CloudVolume(dest_layer_path)
+ dvol = CloudVolume(dest_layer_path, mip=mip)
except Exception: # no info file
info = copy.deepcopy(vol.info)
dvol = CloudVolume(dest_layer_path, info=info)
dvol.commit_info()
- if chunk_size is not None:
- dvol.info['scales'] = dvol.info['scales'][:1]
- dvol.info['scales'][0]['chunk_sizes'] = [ chunk_size.tolist() ]
- dvol.commit_info()
+ dvol.info['scales'] = dvol.info['scales'][:mip+1]
+ dvol.info['scales'][mip]['chunk_sizes'] = [ chunk_size.tolist() ]
+ dvol.commit_info()
- create_downsample_scales(dest_layer_path, mip=0, ds_shape=shape, preserve_chunk_size=True)
+ create_downsample_scales(dest_layer_path,
+ mip=mip, ds_shape=shape, preserve_chunk_size=preserve_chunk_size)
- bounds = vol.bounds.clone()
- for startpt in tqdm(xyzrange( bounds.minpt, bounds.maxpt, shape ), desc="Inserting Transfer Tasks"):
+ if bounds is None:
+ bounds = vol.bounds.clone()
+ else:
+ bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
+ bounds = Bbox.clamp(bounds, vol.bounds)
+
+ total = int(reduce(operator.mul, np.ceil(bounds.size3() / shape)))
+ for startpt in tqdm(xyzrange( bounds.minpt, bounds.maxpt, shape ), desc="Inserting Transfer Tasks", total=total):
task = TransferTask(
src_path=src_layer_path,
dest_path=dest_layer_path,
@@ -285,12 +372,12 @@ def create_transfer_tasks(
offset=startpt.clone(),
fill_missing=fill_missing,
translate=translate,
+ mip=mip,
)
task_queue.insert(task)
task_queue.wait('Uploading Transfer Tasks')
- dvol = CloudVolume(dest_layer_path)
- dvol.provenance.processing.append({
+ job_details = {
'method': {
'task': 'TransferTask',
'src': src_layer_path,
@@ -298,14 +385,31 @@ def create_transfer_tasks(
'shape': list(map(int, shape)),
'fill_missing': fill_missing,
'translate': list(map(int, translate)),
+ 'bounds': [
+ bounds.minpt.tolist(),
+ bounds.maxpt.tolist()
+ ],
+ 'mip': mip,
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
- })
+ }
+
+ dvol = CloudVolume(dest_layer_path)
+ dvol.provenance.sources = [ src_layer_path ]
+ dvol.provenance.processing.append(job_details)
dvol.commit_provenance()
-def create_contrast_normalization_tasks(task_queue, src_path, dest_path,
- shape=None, mip=0, clip_fraction=0.01, fill_missing=False, translate=(0,0,0)):
+ if vol.path.protocol != 'boss':
+ vol.provenance.processing.append(job_details)
+ vol.commit_provenance()
+
+def create_contrast_normalization_tasks(
+ task_queue, src_path, dest_path, levels_path=None,
+ shape=None, mip=0, clip_fraction=0.01,
+ fill_missing=False, translate=(0,0,0),
+ minval=None, maxval=None
+ ):
srcvol = CloudVolume(src_path, mip=mip)
@@ -332,12 +436,15 @@ def create_contrast_normalization_tasks(task_queue, src_path, dest_path,
task = ContrastNormalizationTask(
src_path=src_path,
dest_path=dest_path,
+ levels_path=levels_path,
shape=task_shape,
offset=startpt.clone(),
clip_fraction=clip_fraction,
mip=mip,
fill_missing=fill_missing,
translate=translate,
+ minval=minval,
+ maxval=maxval,
)
task_queue.insert(task)
task_queue.wait('Uploading Contrast Normalization Tasks')
@@ -351,64 +458,91 @@ def create_contrast_normalization_tasks(task_queue, src_path, dest_path,
'clip_fraction': clip_fraction,
'mip': mip,
'translate': Vec(*translate).tolist(),
+ 'minval': minval,
+ 'maxval': maxval,
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
dvol.commit_provenance()
-def create_luminance_levels_tasks(task_queue, layer_path, coverage_factor=0.01, shape=None, offset=(0,0,0), mip=0):
- vol = CloudVolume(layer_path)
+def create_luminance_levels_tasks(
+ task_queue, layer_path,
+ levels_path=None, coverage_factor=0.01,
+ shape=None, offset=(0,0,0), mip=0, bounds=None
+ ):
+ """
+ Compute per slice luminance level histogram and write them as
+ $layer_path/levels/$z. Each z file looks like:
+
+ {
+ "levels": [ 0, 35122, 12, ... ], # 256 indices, index = luminance i.e. 0 is black, 255 is white
+ "patch_size": [ sx, sy, sz ], # metadata on how large the patches were
+ "num_patches": 20, # metadata on
+ "coverage_ratio": 0.011, # actual sampled area on this slice normalized by ROI size.
+ }
+
+ layer_path: source image to sample from
+ levels_path: which path to write ./levels/ to (default: $layer_path)
+ coverage_factor: what fraction of the image to sample
+
+ offset & shape: Allows you to specify an ROI if much of
+ the edges are black. Defaults to entire image.
+ mip: int, which mip to work with, default maximum resolution
+ """
+ vol = CloudVolume(layer_path, mip=mip)
if shape == None:
shape = vol.shape.clone()
shape.z = 1
offset = Vec(*offset)
+ zoffset = offset.clone()
- for z in range(vol.bounds.minpt.z, vol.bounds.maxpt.z + 1):
- offset.z = z
+ if bounds is None:
+ bounds = vol.bounds.clone()
+ else:
+ bounds = vol.bbox_to_mip(bounds, mip=0, to_mip=mip)
+ bounds = Bbox.clamp(bounds, vol.bounds)
+
+ for z in range(bounds.minpt.z, bounds.maxpt.z + 1):
+ zoffset.z = z
task = LuminanceLevelsTask(
src_path=layer_path,
+ levels_path=levels_path,
shape=shape,
- offset=offset,
+ offset=zoffset,
coverage_factor=coverage_factor,
mip=mip,
)
task_queue.insert(task)
task_queue.wait('Uploading Luminance Levels Tasks')
- vol.provenance.processing.append({
- 'method': {
- 'task': 'LuminanceLevelsTask',
- 'src': layer_path,
- 'shape': Vec(*shape).tolist(),
- 'offset': Vec(*offset).tolist(),
- 'coverage_factor': coverage_factor,
- 'mip': mip,
- },
- 'by': USER_EMAIL,
- 'date': strftime('%Y-%m-%d %H:%M %Z'),
- })
- vol.commit_provenance()
-
-def create_boss_transfer_tasks(task_queue, src_layer_path, dest_layer_path, shape=Vec(1024, 1024, 64)):
- # Note: Weird errors with datatype changing to float64 when requesting 2048,2048,64
- # 1024,1024,64 worked nicely though.
- shape = Vec(*shape)
- vol = CloudVolume(dest_layer_path)
-
- create_downsample_scales(dest_layer_path, mip=0, ds_shape=shape)
+ if levels_path:
+ try:
+ vol = CloudVolume(levels_path)
+ except cloudvolume.exceptions.InfoUnavailableError:
+ vol = CloudVolume(levels_path, info=vol.info)
- for startpt in tqdm(xyzrange( vol.bounds.minpt, vol.bounds.maxpt, shape ), desc="Inserting Boss Transfer Tasks"):
- task = BossTransferTask(
- src_path=src_layer_path,
- dest_path=dest_layer_path,
- shape=shape.clone(),
- offset=startpt.clone(),
- )
- task_queue.insert(task)
- task_queue.wait('Uploading Boss Transfer Tasks')
+ if vol.path.protocol != 'boss':
+ vol.provenance.processing.append({
+ 'method': {
+ 'task': 'LuminanceLevelsTask',
+ 'src': layer_path,
+ 'levels_path': levels_path,
+ 'shape': Vec(*shape).tolist(),
+ 'offset': Vec(*offset).tolist(),
+ 'bounds': [
+ bounds.minpt.tolist(),
+ bounds.maxpt.tolist()
+ ],
+ 'coverage_factor': coverage_factor,
+ 'mip': mip,
+ },
+ 'by': OPERATOR_CONTACT,
+ 'date': strftime('%Y-%m-%d %H:%M %Z'),
+ })
+ vol.commit_provenance()
def create_watershed_remap_tasks(task_queue, map_path, src_layer_path, dest_layer_path, shape=Vec(2048, 2048, 64)):
shape = Vec(*shape)
@@ -435,7 +569,7 @@ def create_watershed_remap_tasks(task_queue, map_path, src_layer_path, dest_laye
'remap_file': map_path,
'shape': list(shape),
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
dvol.commit_provenance()
@@ -468,6 +602,7 @@ def create_fixup_downsample_tasks(task_queue, layer_path, points, shape=Vec(2048
)
task_queue.insert(task)
task_queue.wait('Uploading')
+
def create_quantized_affinity_info(src_layer, dest_layer, shape, mip, chunk_size):
srcvol = CloudVolume(src_layer)
@@ -516,7 +651,7 @@ def create_quantize_tasks(
'fill_missing': fill_missing,
'mip': mip,
},
- 'by': USER_EMAIL,
+ 'by': OPERATOR_CONTACT,
'date': strftime('%Y-%m-%d %H:%M %Z'),
})
destvol.commit_provenance()
@@ -741,6 +876,7 @@ def create_inference_tasks(task_queue, image_layer_path, convnet_model_path,
})
vol.commit_provenance()
+
def upload_build_chunks(storage, volume, offset=[0, 0, 0], build_chunk_size=[1024,1024,128]):
offset = Vec(*offset)
shape = Vec(*volume.shape[:3])
diff --git a/igneous/tasks.py b/igneous/tasks.py
index d358146e..a5fcf6b4 100755
--- a/igneous/tasks.py
+++ b/igneous/tasks.py
@@ -211,21 +211,30 @@ def _download_input_chunk(self, bounds):
class DeleteTask(RegisteredTask):
"""Delete a block of images inside a layer on all mip levels."""
- def __init__(self, layer_path, shape, offset):
- super(DeleteTask, self).__init__(layer_path, shape, offset)
+ def __init__(self, layer_path, shape, offset, mip=0, num_mips=5):
+ super(DeleteTask, self).__init__(layer_path, shape, offset, mip, num_mips)
self.layer_path = layer_path
self.shape = Vec(*shape)
self.offset = Vec(*offset)
+ self.mip = mip
+ self.num_mips = num_mips
def execute(self):
- vol = CloudVolume(self.layer_path)
+ vol = CloudVolume(self.layer_path, mip=self.mip)
highres_bbox = Bbox( self.offset, self.offset + self.shape )
- for mip in vol.available_mips:
+
+ top_mip = min(vol.available_mips[-1], self.mip + self.num_mips)
+
+ for mip in range(self.mip, top_mip + 1):
vol.mip = mip
- bbox = vol.bbox_to_mip(highres_bbox, 0, mip)
+ bbox = vol.bbox_to_mip(highres_bbox, self.mip, mip)
bbox = bbox.round_to_chunk_size(vol.underlying, offset=vol.bounds.minpt)
bbox = Bbox.clamp(bbox, vol.bounds)
+
+ if bbox.volume() == 0:
+ continue
+
vol.delete(bbox)
@@ -294,15 +303,19 @@ def __init__(self, shape, offset, layer_path, **kwargs):
'mip': kwargs.get('mip', 0),
'simplification_factor': kwargs.get('simplification_factor', 100),
'max_simplification_error': kwargs.get('max_simplification_error', 40),
+ 'mesh_dir': kwargs.get('mesh_dir', None),
'remap_table': kwargs.get('remap_table', None),
'generate_manifests': kwargs.get('generate_manifests', False),
'low_padding': kwargs.get('low_padding', 0),
- 'high_padding': kwargs.get('high_padding', 1)
+ 'high_padding': kwargs.get('high_padding', 1),
+ 'parallel_download': kwargs.get('parallel_download', 1),
+ 'cache_control': kwargs.get('cache_control', None)
}
def execute(self):
self._volume = CloudVolume(
- self.layer_path, self.options['mip'], bounded=False)
+ self.layer_path, self.options['mip'], bounded=False,
+ parallel=self.options['parallel_download'])
self._bounds = Bbox(self.offset, self.shape + self.offset)
self._bounds = Bbox.clamp(self._bounds, self._volume.bounds)
@@ -316,8 +329,8 @@ def execute(self):
data_bounds.maxpt += self.options['high_padding']
self._mesh_dir = None
- if 'meshing' in self._volume.info:
- self._mesh_dir = self._volume.info['meshing']
+ if self.options['mesh_dir'] is not None:
+ self._mesh_dir = self.options['mesh_dir']
elif 'mesh' in self._volume.info:
self._mesh_dir = self._volume.info['mesh']
@@ -358,6 +371,7 @@ def _compute_meshes(self):
),
content=self._create_mesh(obj_id),
compress=True,
+ cache_control=self.options['cache_control']
)
if self.options['generate_manifests']:
@@ -369,7 +383,8 @@ def _compute_meshes(self):
file_path='{}/{}:{}'.format(
self._mesh_dir, remapped_id, self.options['lod']),
content=json.dumps({"fragments": fragments}),
- content_type='application/json'
+ content_type='application/json',
+ cache_control=self.options['cache_control']
)
def _create_mesh(self, obj_id):
@@ -413,20 +428,18 @@ class MeshManifestTask(RegisteredTask):
a single mesh ['0:','1:',..'9:']
"""
- def __init__(self, layer_path, prefix, lod=0):
+ def __init__(self, layer_path, prefix, lod=0, mesh_dir=None):
super(MeshManifestTask, self).__init__(layer_path, prefix)
self.layer_path = layer_path
self.lod = lod
self.prefix = prefix
+ self.mesh_dir = mesh_dir
def execute(self):
with Storage(self.layer_path) as storage:
self._info = json.loads(storage.get_file('info').decode('utf8'))
- self.mesh_dir = None
- if 'meshing' in self._info:
- self.mesh_dir = self._info['meshing']
- elif 'mesh' in self._info:
+ if self.mesh_dir is None and 'mesh' in self._info:
self.mesh_dir = self._info['mesh']
self._generate_manifests(storage)
@@ -752,9 +765,17 @@ class ContrastNormalizationTask(RegisteredTask):
"""TransferTask + Contrast Correction based on LuminanceLevelsTask output."""
# translate = change of origin
- def __init__(self, src_path, dest_path, shape, offset, mip, clip_fraction, fill_missing, translate):
- super(ContrastNormalizationTask, self).__init__(src_path, dest_path,
- shape, offset, mip, clip_fraction, fill_missing, translate)
+ def __init__(
+ self, src_path, dest_path, levels_path, shape,
+ offset, mip, clip_fraction, fill_missing,
+ translate, minval, maxval
+ ):
+
+ super(ContrastNormalizationTask, self).__init__(
+ src_path, dest_path, levels_path, shape, offset,
+ mip, clip_fraction, fill_missing, translate,
+ minval, maxval
+ )
self.src_path = src_path
self.dest_path = dest_path
self.shape = Vec(*shape)
@@ -763,6 +784,10 @@ def __init__(self, src_path, dest_path, shape, offset, mip, clip_fraction, fill_
self.translate = Vec(*translate)
self.mip = int(mip)
self.clip_fraction = float(clip_fraction)
+ self.minval = minval
+ self.maxval = maxval
+
+ self.levels_path = levels_path if levels_path else self.src_path
assert 0 <= self.clip_fraction <= 1
@@ -793,7 +818,11 @@ def execute(self):
image[:, :, imagez] = img
image = np.round(image)
- image = np.clip(image, 0.0, maxval).astype(destcv.dtype)
+
+ minval = self.minval if self.minval is not None else 0.0
+ maxval = self.maxval if self.maxval is not None else maxval
+
+ image = np.clip(image, minval, maxval).astype(destcv.dtype)
bounds += self.translate
downsample_and_upload(image, bounds, destcv, self.shape)
@@ -831,37 +860,48 @@ def find_section_clamping_values(self, zlevel, lowerfract, upperfract):
def fetch_z_levels(self):
bounds = Bbox(self.offset, self.shape[:3] + self.offset)
- levelfilenames = ['levels/{}/{}'.format(self.mip, z)
- for z in range(bounds.minpt.z, bounds.maxpt.z + 1)]
- with Storage(self.src_path) as stor:
+
+ levelfilenames = [
+ 'levels/{}/{}'.format(self.mip, z) \
+ for z in range(bounds.minpt.z, bounds.maxpt.z + 1)
+ ]
+
+ with Storage(self.levels_path) as stor:
levels = stor.get_files(levelfilenames)
- errors = [level['filename']
- for level in levels if level['content'] == None]
+ errors = [
+ level['filename'] \
+ for level in levels if level['content'] == None
+ ]
+
if len(errors):
raise Exception(", ".join(
errors) + " were not defined. Did you run a LuminanceLevelsTask for these slices?")
levels = [(
- int(os.path.basename(item['filename'])),
- json.loads(item['content'].decode('utf-8'))
- ) for item in levels]
+ int(os.path.basename(item['filename'])),
+ json.loads(item['content'].decode('utf-8'))
+ ) for item in levels ]
+
levels.sort(key=lambda x: x[0])
levels = [x[1] for x in levels]
- return [np.array(x['levels'], dtype=np.uint64) for x in levels]
+ return [ np.array(x['levels'], dtype=np.uint64) for x in levels ]
class LuminanceLevelsTask(RegisteredTask):
"""Generate a frequency count of luminance values by random sampling. Output to $PATH/levels/$MIP/$Z"""
- def __init__(self, src_path, shape, offset, coverage_factor, mip):
+ def __init__(self, src_path, levels_path, shape, offset, coverage_factor, mip):
super(LuminanceLevelsTask, self).__init__(
- src_path, shape, offset, coverage_factor, mip)
+ src_path, levels_path, shape,
+ offset, coverage_factor, mip
+ )
self.src_path = src_path
self.shape = Vec(*shape)
self.offset = Vec(*offset)
self.coverage_factor = coverage_factor
self.mip = int(mip)
+ self.levels_path = levels_path
assert 0 < coverage_factor <= 1, "Coverage Factor must be between 0 and 1"
@@ -888,18 +928,19 @@ def execute(self):
biggest = bboxes[-1][1]
output = {
- "levels": levels.tolist(),
- "patch_size": biggest.tolist(),
- "num_patches": len(bboxes),
- "coverage_ratio": covered_area / self.shape.rectVolume(),
+ "levels": levels.tolist(),
+ "patch_size": biggest.tolist(),
+ "num_patches": len(bboxes),
+ "coverage_ratio": covered_area / self.shape.rectVolume(),
}
- levels_path = os.path.join(self.src_path, 'levels')
- with Storage(levels_path, n_threads=0) as stor:
+ path = self.levels_path if self.levels_path else self.src_path
+ path = os.path.join(path, 'levels')
+ with Storage(path, n_threads=0) as stor:
stor.put_json(
- file_path="{}/{}".format(self.mip, self.offset.z),
- content=output,
- cache_control='no-cache'
+ file_path="{}/{}".format(self.mip, self.offset.z),
+ content=output,
+ cache_control='no-cache'
)
def select_bounding_boxes(self, dataset_bounds):
@@ -935,25 +976,33 @@ def select_bounding_boxes(self, dataset_bounds):
class TransferTask(RegisteredTask):
# translate = change of origin
- def __init__(self, src_path, dest_path, shape, offset, fill_missing, translate):
+ def __init__(
+ self, src_path, dest_path,
+ shape, offset, fill_missing,
+ translate, mip=0
+ ):
super(TransferTask, self).__init__(
- src_path, dest_path, shape, offset, fill_missing, translate)
+ src_path, dest_path, shape,
+ offset, fill_missing, translate,
+ mip
+ )
self.src_path = src_path
self.dest_path = dest_path
self.shape = Vec(*shape)
self.offset = Vec(*offset)
self.fill_missing = fill_missing
self.translate = Vec(*translate)
+ self.mip = int(mip)
def execute(self):
- srccv = CloudVolume(self.src_path, fill_missing=self.fill_missing)
- destcv = CloudVolume(self.dest_path, fill_missing=self.fill_missing)
+ srccv = CloudVolume(self.src_path, fill_missing=self.fill_missing, mip=self.mip)
+ destcv = CloudVolume(self.dest_path, fill_missing=self.fill_missing, mip=self.mip)
bounds = Bbox(self.offset, self.shape + self.offset)
bounds = Bbox.clamp(bounds, srccv.bounds)
image = srccv[bounds.to_slices()]
bounds += self.translate
- downsample_and_upload(image, bounds, destcv, self.shape)
+ downsample_and_upload(image, bounds, destcv, self.shape, mip=self.mip)
class WatershedRemapTask(RegisteredTask):
@@ -1491,6 +1540,3 @@ def _upload_log(self):
content=json.dumps(self.log),
content_type='application/json'
)
-
-
-
diff --git a/version.py b/igneous_version.py
similarity index 100%
rename from version.py
rename to igneous_version.py
diff --git a/requirements.txt b/requirements.txt
index fa80ab6f..8f3dae7a 100755
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,19 +1,10 @@
-backports.lzma==0.0.8
-click==6.7
-cryptography==2.3
-#cloud-volume>=0.31.1
-intern
+click>=6.7
+cloud-volume>=0.38.0
google-cloud-logging
-google-api-python-client==1.6.2
-networkx==2.1
numpy>=1.14.2
-pyasn1
-pyopenssl==17.2.0
+Pillow>=4.2.1
pytest>=3.3.1
-scipy>=1.1.0
task-queue>=0.4.1
-tenacity>=4.10.0
-e git+https://github.com/seung-lab/tqdm.git#egg=tqdm
oauth2client==3.0.0
-protobuf>=3.5.1
scikit-image>=0.14.1
diff --git a/setup.py b/setup.py
index 2e32980a..5a6f5404 100755
--- a/setup.py
+++ b/setup.py
@@ -16,7 +16,11 @@
third_party_dir = './ext/third_party'
setuptools.setup(
- setup_requires=['pbr'],
+ setup_requires=['pbr', 'numpy'],
+ extras_require={
+ ':python_version == "2.7"': ['futures'],
+ ':python_version == "2.6"': ['futures'],
+ },
pbr=True,
ext_modules=[
setuptools.Extension(
diff --git a/test/test_tasks.py b/test/test_tasks.py
index fc17091d..eca0bb13 100755
--- a/test/test_tasks.py
+++ b/test/test_tasks.py
@@ -1,4 +1,5 @@
from builtins import range
+from collections import defaultdict
import json
import os.path
import shutil
@@ -14,6 +15,7 @@
DeleteTask, InferenceTask
)
from igneous import downsample, validate_by_template_matching
+import igneous.task_creation as tc
from igneous.task_creation import create_downsample_scales, create_downsampling_tasks, create_quantized_affinity_info
from .layer_harness import delete_layer, create_layer
@@ -384,7 +386,40 @@ def test_mesh_manifests():
if os.path.exists(directory):
shutil.rmtree(directory)
-
+
+def test_luminance_levels_task():
+ directory = '/tmp/removeme/luminance_levels/'
+ layer_path = 'file://' + directory
+
+ delete_layer(layer_path)
+
+ storage, imgd = create_layer(
+ size=(256,256,128,1), offset=(0,0,0),
+ layer_type="image", layer_name='luminance_levels'
+ )
+
+ with MockTaskQueue() as tq:
+ tc.create_luminance_levels_tasks(tq,
+ layer_path=layer_path,
+ coverage_factor=0.01,
+ shape=None,
+ offset=(0,0,0),
+ mip=0
+ )
+
+
+ gt = [ 0 ] * 256
+ for x,y,z in lib.xyzrange( (0,0,0), list(imgd.shape[:2]) + [1] ):
+ gt[ imgd[x,y,0,0] ] += 1
+
+
+ with open('/tmp/removeme/luminance_levels/levels/0/0', 'rt') as f:
+ levels = f.read()
+
+ levels = json.loads(levels)
+ assert levels['coverage_ratio'] == 1.0
+ assert levels['levels'] == gt
+
# def test_watershed():
# return # needs expensive julia stuff enabled in dockerfile