def generate_screenshot(filename, typeid):
metadata = get_file_metadata(filename)
hash = metadata['types'][typeid]['hash']
subfiles = metadata['types'][typeid]['subfiles']
dae_data = get_hash(hash)['data']
subfile_map = {}
for subfile in subfiles:
img_meta = get_file_metadata(subfile)
img_hash = img_meta['hash']
img_data = get_hash(img_hash)['data']
base_name = os.path.basename(os.path.split(subfile)[0])
subfile_map[base_name] = img_data
#The below is a total hack and I feel really dirty doing it, but
# there is no way to get panda3d to clean up after itself except to
# exit the process. Celery workers are run as a daemon, so they can't
# create child processes. Doing so could cause orphaned, defunct processes.
# I'm doing it anyway because I haven't found any other way to do this. Sorry.
q = multiprocessing.Queue()
daemonic = multiprocessing.current_process()._daemonic
multiprocessing.current_process()._daemonic = False
p = multiprocessing.Process(target=_get_screenshot, args=[q, dae_data, subfile_map])
p.start()
main_screenshot = q.get()
p.join()
multiprocessing.current_process()._daemonic = daemonic
im = Image.open(StringIO(main_screenshot))
thumbnail = StringIO()
im.thumbnail((96,96), Image.ANTIALIAS)
im.save(thumbnail, "PNG", optimize=1)
thumbnail = thumbnail.getvalue()
main_key = hashlib.sha256(main_screenshot).hexdigest()
thumb_key = hashlib.sha256(thumbnail).hexdigest()
save_file_data(main_key, main_screenshot, "image/png")
save_file_data(thumb_key, thumbnail, "image/png")
ss_info = {'screenshot': main_key, 'thumbnail': thumb_key}
base_filename, version_num = os.path.split(filename)
add_metadata(base_filename, version_num, typeid, ss_info)
def generate_progressive_errors(filename, typeid):
if typeid != 'progressive':
return
metadata = get_file_metadata(filename)
hash = metadata['types'][typeid]['hash']
subfiles = metadata['types'][typeid]['subfiles']
progressive_stream_hash = metadata['types'][typeid]['progressive_stream']
mipmap_tar_hash = metadata['types'][typeid]['mipmaps'].values()[0]['hash']
dae_data = get_hash(hash)['data']
pm_data = get_hash(progressive_stream_hash)['data'] if progressive_stream_hash is not None else None
mipmap_tar_data = get_hash(mipmap_tar_hash)['data']
#The below is a total hack and I feel really dirty doing it, but
# there is no way to get panda3d to clean up after itself except to
# exit the process. Celery workers are run as a daemon, so they can't
# create child processes. Doing so could cause orphaned, defunct processes.
# I'm doing it anyway because I haven't found any other way to do this. Sorry.
q = multiprocessing.Queue()
daemonic = multiprocessing.current_process()._daemonic
multiprocessing.current_process()._daemonic = False
p = multiprocessing.Process(target=_get_progressive_errors, args=[q, dae_data, pm_data, mipmap_tar_data])
p.start()
success, error_data = q.get()
p.join()
multiprocessing.current_process()._daemonic = daemonic
if not success:
print 'Exception from worker, %s' % str(error_data)
raise Exception("got exception from worker: %s" % str(error_data))
if error_data is None:
return
error_info = {'progressive_perceptual_error': error_data}
base_filename, version_num = os.path.split(filename)
add_metadata(base_filename, version_num, typeid, error_info)
def generate_metadata(filename, typeid):
metadata = get_file_metadata(filename)
hash = metadata['types'][typeid]['hash']
subfiles = metadata['types'][typeid]['subfiles']
dae_data = get_hash(hash)['data']
subfile_map = {}
subfile_sizes = {}
subfile_sizes_gzip = {}
for subfile in subfiles:
img_meta = get_file_metadata(subfile)
img_hash = img_meta['hash']
img_data = get_hash(img_hash)['data']
subfile_sizes[subfile] = len(img_data)
subfile_sizes_gzip[subfile] = get_gzip_size(img_data)
base_name = os.path.basename(os.path.split(subfile)[0])
subfile_map[base_name] = img_data
def customImageLoader(filename):
return subfile_map[posixpath.basename(filename)]
mesh = collada.Collada(StringIO(dae_data), aux_file_loader=customImageLoader)
stream_hash = metadata['types'][typeid].get('progressive_stream', None)
stream_data = get_hash(stream_hash)['data'] if stream_hash is not None else None
if stream_data is not None:
# add back the progressive stream so we get accurate metadata
mesh = add_back_pm(mesh, StringIO(stream_data), 100)
json_data = json.loads(getJSON(mesh))
metadata_info = {}
metadata_info['num_triangles'] = json_data['num_triangles']
metadata_info['num_materials'] = len(json_data['materials'])
metadata_info['num_images'] = len(json_data['images'])
metadata_info['texture_ram_usage'] = json_data['texture_ram']
metadata_info['num_draw_calls'] = json_data['num_draw_with_batching']
metadata_info['num_vertices'] = json_data['num_vertices']
metadata_info['bounds_info'] = json_data['bounds_info']
triangulate = meshtool.filters.factory.getInstance('triangulate')
mesh = triangulate.apply(mesh)
save_ply = meshtool.filters.factory.getInstance('save_ply')
ply_temp_file = tempfile.mktemp(suffix='.ply', prefix='meshtool-genmetadata-zernike')
save_ply.apply(mesh, ply_temp_file)
zernike_calc = os.path.join(os.path.dirname(__file__), 'zernike_calculator')
zernike_output = subprocess.check_output([zernike_calc, ply_temp_file])
zernike_nums = zernike_output.split(',')
zernike_nums = map(float, zernike_nums)
metadata_info['zernike'] = zernike_nums
os.remove(ply_temp_file)
split = filename.split("/")
version = split[-1:][0]
file_key = "/".join(split[:-1])
added_metadata = { 'metadata': metadata_info }
# the size of the mesh, gzipped
added_metadata['size_gzip'] = get_gzip_size(dae_data)
# the size of each subfile
added_metadata['subfile_sizes'] = subfile_sizes
# the size of each subfile, gzipped
added_metadata['subfile_sizes_gzip'] = subfile_sizes_gzip
if stream_data is not None:
# the size of the progressive stream, if exists
added_metadata['progressive_stream_size'] = len(stream_data)
added_metadata['progressive_stream_size_gzip'] = get_gzip_size(stream_data)
add_metadata(file_key, version, typeid, added_metadata)
def generate_panda3d(filename, typeid):
metadata = get_file_metadata(filename)
hash = metadata['types'][typeid]['hash']
subfiles = metadata['types'][typeid]['subfiles']
progressive_stream = metadata['types'][typeid].get('progressive_stream')
progressive_data = get_hash(progressive_stream)['data'] if progressive_stream else None
mipmaps = metadata['types'][typeid].get('mipmaps')
pathinfo = PathInfo(filename)
dae_data = get_hash(hash)['data']
if mipmaps is not None:
mipmap_data = {}
for mipmap_name, mipmap_info in mipmaps.iteritems():
tar_hash = mipmap_info['hash']
tar_data = get_hash(tar_hash)['data']
min_range = None
max_range = None
min_size = 128
for byte_range in mipmap_info['byte_ranges']:
if byte_range['width'] <= min_size and byte_range['height'] <= min_size:
min_range = (byte_range['offset'], byte_range['length'])
max_range = (byte_range['offset'], byte_range['length'])
mipmap_data[mipmap_name] = {}
mipmap_data[mipmap_name]['base'] = tar_data[min_range[0]:min_range[0]+min_range[1]]
mipmap_data[mipmap_name]['full'] = tar_data[max_range[0]:max_range[0]+max_range[1]]
def base_loader(filename):
return mipmap_data[filename]['base']
def full_loader(filename):
return mipmap_data[filename]['full']
base_mesh = collada.Collada(StringIO(dae_data), aux_file_loader=base_loader)
base_bam_data = getBam(base_mesh, 'base_' + filename)
base_bam_hex_key = hashlib.sha256(base_bam_data).hexdigest()
save_file_data(base_bam_hex_key, base_bam_data, "model/x-bam")
full_mesh = collada.Collada(StringIO(dae_data), aux_file_loader=full_loader)
if progressive_data is not None:
full_mesh = add_back_pm.add_back_pm(full_mesh, StringIO(progressive_data), 100)
full_bam_data = getBam(full_mesh, 'full_' + filename)
full_bam_hex_key = hashlib.sha256(full_bam_data).hexdigest()
save_file_data(full_bam_hex_key, full_bam_data, "model/x-bam")
add_metadata(pathinfo.basepath, pathinfo.version, typeid, {'panda3d_base_bam': base_bam_hex_key,
'panda3d_full_bam': full_bam_hex_key})
else:
subfile_map = {}
for subfile in subfiles:
img_meta = get_file_metadata(subfile)
img_hash = img_meta['hash']
img_data = get_hash(img_hash)['data']
base_name = os.path.basename(os.path.split(subfile)[0])
subfile_map[base_name] = img_data
def customImageLoader(filename):
return subfile_map[posixpath.basename(filename)]
mesh = collada.Collada(StringIO(dae_data), aux_file_loader=customImageLoader)
other_bam_data = getBam(mesh, typeid + '_' + filename)
other_bam_hex_key = hashlib.sha256(other_bam_data).hexdigest()
save_file_data(other_bam_hex_key, other_bam_data, "model/x-bam")
add_metadata(pathinfo.basepath, pathinfo.version, typeid, {'panda3d_bam': other_bam_hex_key})
def generate_progressive(filename, typeid):
metadata = get_file_metadata(filename)
hash = metadata['types'][typeid]['hash']
subfiles = metadata['types'][typeid]['subfiles']
path, version = posixpath.split(filename)
dae_data = get_hash(hash)['data']
subfile_map = {}
for subfile in subfiles:
img_meta = get_file_metadata(subfile)
img_hash = img_meta['hash']
img_data = get_hash(img_hash)['data']
base_name = posixpath.basename(posixpath.split(subfile)[0])
subfile_map[base_name] = img_data
def customImageLoader(filename):
return subfile_map[posixpath.basename(filename)]
mesh = collada.Collada(StringIO(dae_data), aux_file_loader=customImageLoader)
strip_lines = meshtool.filters.factory.getInstance('strip_lines')
mesh = strip_lines.apply(mesh)
med_opts = meshtool.filters.factory.getInstance('medium_optimizations')
mesh = med_opts.apply(mesh)
progressive_stream = StringIO()
sander_simplify = SanderSimplify(mesh, progressive_stream)
mesh = sander_simplify.simplify()
if sander_simplify.base_tri_count != sander_simplify.orig_tri_count:
progressive_stream = progressive_stream.getvalue()
progressive_hex_key = hashlib.sha256(progressive_stream).hexdigest()
save_file_data(progressive_hex_key, progressive_stream, "model/vnd.pdae")
progressive_stream_num_triangles = sander_simplify.orig_tri_count - sander_simplify.base_tri_count
else:
progressive_hex_key = None
progressive_stream_num_triangles = 0
mipmap_metadata = {}
mipmaps = getMipMaps(mesh)
for imgpath, (tarbuf, ranges) in mipmaps.iteritems():
mipmap_tar_hex_key = hashlib.sha256(tarbuf).hexdigest()
save_file_data(mipmap_tar_hex_key, tarbuf, "application/x-tar")
mipmap_metadata[imgpath] = {'hash':mipmap_tar_hex_key, 'byte_ranges':ranges}
#Make sure image paths are just the base name
current_prefix = "progressive"
subfile_names = []
subfile_map = {}
for img in mesh.images:
base_name = posixpath.basename(img.path)
subfile_map[base_name] = img.data
img_hex_key = hashlib.sha256(subfile_map[base_name]).hexdigest()
save_file_data(img_hex_key, subfile_map[base_name], "image/%s" % img.pilimage.format.lower())
img_path = "%s/%s/%s" % (path, current_prefix, base_name)
img_len = len(subfile_map[base_name])
img_version_num = get_new_version_from_path(img_path, file_type="image")
save_file_name(img_path, img_version_num, img_hex_key, img_len)
subfile_names.append("%s/%s" % (img_path, img_version_num))
str_buffer = StringIO()
mesh.write(str_buffer)
orig_save_data = str_buffer.getvalue()
orig_hex_key = hashlib.sha256(orig_save_data).hexdigest()
save_file_data(orig_hex_key, orig_save_data, "application/xml")
zip_buffer = StringIO()
combined_zip = zipfile.ZipFile(zip_buffer, mode='w', compression=zipfile.ZIP_DEFLATED)
combined_zip.writestr(posixpath.basename(path), orig_save_data)
for img_name, img_data in subfile_map.iteritems():
combined_zip.writestr(img_name, img_data)
combined_zip.close()
zip_save_data = zip_buffer.getvalue()
zip_hex_key = hashlib.sha256(zip_save_data).hexdigest()
save_file_data(zip_hex_key, zip_save_data, "application/zip")
save_version_type(path, version, orig_hex_key, len(orig_save_data),
subfile_names, zip_hex_key, "progressive")
add_metadata(path, version, "progressive", { 'progressive_stream': progressive_hex_key,
'progressive_stream_num_triangles': progressive_stream_num_triangles,
'mipmaps': mipmap_metadata })
send_task("celery_tasks.generate_screenshot.generate_screenshot", args=[filename, "progressive"])
send_task("celery_tasks.generate_metadata.generate_metadata", args=[filename, "progressive"])