Meshroom/meshroom/nodes/aliceVision/SketchfabUpload.py
2024-09-16 17:50:54 +02:00

275 lines
9.9 KiB
Python

__version__ = "1.0"
from meshroom.core import desc
from meshroom.core.utils import VERBOSE_LEVEL
import glob
import os
import json
import zipfile
import requests
import io
class BufferReader(io.BytesIO): # object to call the callback while the file is being uploaded
def __init__(self, buf=b'',
callback=None,
cb_args=(),
cb_kwargs={},
stopped=None):
self._callback = callback
self._cb_args = cb_args
self._cb_kwargs = cb_kwargs
self._stopped = stopped
self._progress = 0
self._len = len(buf)
io.BytesIO.__init__(self, buf)
def __len__(self):
return self._len
def read(self, n=-1):
chunk = io.BytesIO.read(self, n)
self._progress += int(len(chunk))
self._cb_kwargs.update({
'size' : self._len,
'progress': self._progress
})
if self._callback:
try:
self._callback(*self._cb_args, **self._cb_kwargs)
except Exception as e: # catches exception from the callback
self._cb_kwargs['logManager'].logger.warning('Error at callback: {}'.format(e))
if self._stopped():
raise RuntimeError('Node stopped by user')
return chunk
def progressUpdate(size=None, progress=None, logManager=None):
if not logManager.progressBar:
logManager.makeProgressBar(size, 'Upload progress:')
logManager.updateProgressBar(progress)
class SketchfabUpload(desc.Node):
size = desc.DynamicNodeSize('inputFiles')
category = 'Export'
documentation = '''
Upload a textured mesh on Sketchfab.
'''
inputs = [
desc.ListAttribute(
elementDesc=desc.File(
name="input",
label="Input",
description="",
value="",
),
name="inputFiles",
label="Input Files",
description="Input Files to export.",
group="",
),
desc.StringParam(
name="apiToken",
label="API Token",
description="Get your token from https://sketchfab.com/settings/password.",
value="",
),
desc.StringParam(
name="title",
label="Title",
description="Title cannot be longer than 48 characters.",
value="",
),
desc.StringParam(
name="description",
label="Description",
description="Description cannot be longer than 1024 characters.",
value="",
),
desc.ChoiceParam(
name="license",
label="License",
description="License label.",
value="CC Attribution",
values=["CC Attribution",
"CC Attribution-ShareAlike",
"CC Attribution-NoDerivs",
"CC Attribution-NonCommercial",
"CC Attribution-NonCommercial-ShareAlike",
"CC Attribution-NonCommercial-NoDerivs"],
),
desc.ListAttribute(
elementDesc=desc.StringParam(
name="tag",
label="Tag",
description="Tag cannot be longer than 48 characters.",
value="",
),
name="tags",
label="Tags",
description="Maximum of 42 separate tags.",
group="",
),
desc.ChoiceParam(
name="category",
label="Category",
description="Adding categories helps improve the discoverability of your model.",
value="none",
values=["none",
"animals-pets",
"architecture",
"art-abstract",
"cars-vehicles",
"characters-creatures",
"cultural-heritage-history",
"electronics-gadgets",
"fashion-style",
"food-drink",
"furniture-home",
"music",
"nature-plants",
"news-politics",
"people",
"places-travel",
"science-technology",
"sports-fitness",
"weapons-military"],
),
desc.BoolParam(
name="isPublished",
label="Publish",
description="If the model is not published, it will be saved as a draft.",
value=False,
),
desc.BoolParam(
name="isInspectable",
label="Inspectable",
description="Allow 2D view in model inspector.",
value=True,
),
desc.BoolParam(
name="isPrivate",
label="Private",
description="Requires a pro account.",
value=False,
),
desc.StringParam(
name="password",
label="Password",
description="Requires a pro account.",
value="",
),
desc.ChoiceParam(
name="verboseLevel",
label="Verbose Level",
description="Verbosity level (fatal, error, warning, info, debug, trace).",
values=VERBOSE_LEVEL,
value="info",
),
]
def upload(self, apiToken, modelFile, data, chunk):
modelEndpoint = 'https://api.sketchfab.com/v3/models'
f = open(modelFile, 'rb')
file = {'modelFile': (os.path.basename(modelFile), f.read())}
file.update(data)
f.close()
(files, contentType) = requests.packages.urllib3.filepost.encode_multipart_formdata(file)
headers = {'Authorization': 'Token {}'.format(apiToken), 'Content-Type': contentType}
body = BufferReader(files, progressUpdate, cb_kwargs={'logManager': chunk.logManager}, stopped=self.stopped)
chunk.logger.info('Uploading...')
try:
r = requests.post(
modelEndpoint, **{'data': body, 'headers': headers})
chunk.logManager.completeProgressBar()
except requests.exceptions.RequestException as e:
chunk.logger.error(u'An error occurred: {}'.format(e))
raise RuntimeError()
if r.status_code != requests.codes.created:
chunk.logger.error(u'Upload failed with error: {}'.format(r.json()))
raise RuntimeError()
def resolvedPaths(self, inputFiles):
paths = []
for inputFile in inputFiles:
if os.path.isdir(inputFile.value):
for path, subdirs, files in os.walk(inputFile.value):
for name in files:
paths.append(os.path.join(path, name))
else:
for f in glob.glob(inputFile.value):
paths.append(f)
return paths
def stopped(self):
return self._stopped
def processChunk(self, chunk):
try:
self._stopped = False
chunk.logManager.start(chunk.node.verboseLevel.value)
uploadFile = ''
if not chunk.node.inputFiles:
chunk.logger.warning('Nothing to upload')
return
if chunk.node.apiToken.value == '':
chunk.logger.error('Need API token.')
raise RuntimeError()
if len(chunk.node.title.value) > 48:
chunk.logger.error('Title cannot be longer than 48 characters.')
raise RuntimeError()
if len(chunk.node.description.value) > 1024:
chunk.logger.error('Description cannot be longer than 1024 characters.')
raise RuntimeError()
tags = [ i.value.replace(' ', '-') for i in chunk.node.tags.value.values() ]
if all(len(i) > 48 for i in tags) and len(tags) > 0:
chunk.logger.error('Tags cannot be longer than 48 characters.')
raise RuntimeError()
if len(tags) > 42:
chunk.logger.error('Maximum of 42 separate tags.')
raise RuntimeError()
data = {
'name': chunk.node.title.value,
'description': chunk.node.description.value,
'license': chunk.node.license.value,
'tags': str(tags),
'isPublished': chunk.node.isPublished.value,
'isInspectable': chunk.node.isInspectable.value,
'private': chunk.node.isPrivate.value,
'password': chunk.node.password.value
}
if chunk.node.category.value != 'none':
data.update({'categories': chunk.node.category.value})
chunk.logger.debug('Data to be sent: {}'.format(str(data)))
# pack files into .zip to reduce file size and simplify process
uploadFile = os.path.join(chunk.node.internalFolder, 'temp.zip')
files = self.resolvedPaths(chunk.node.inputFiles.value)
zf = zipfile.ZipFile(uploadFile, 'w')
for file in files:
zf.write(file, os.path.basename(file))
zf.close()
chunk.logger.debug('Files added to zip: {}'.format(str(files)))
chunk.logger.debug('Created {}'.format(uploadFile))
chunk.logger.info('File size: {}MB'.format(round(os.path.getsize(uploadFile)/(1024*1024), 3)))
self.upload(chunk.node.apiToken.value, uploadFile, data, chunk)
chunk.logger.info('Upload successful. Your model is being processed on Sketchfab. It may take some time to show up on your "models" page.')
except Exception as e:
chunk.logger.error(e)
raise RuntimeError()
finally:
if os.path.isfile(uploadFile):
os.remove(uploadFile)
chunk.logger.debug('Deleted {}'.format(uploadFile))
chunk.logManager.end()
def stopProcess(self, chunk):
self._stopped = True