def multi_get_files(request, fieldname, noajax=False):
"""
View to retrieve MultiuploaderFiles based on a list of ids.
"""
if request.method == 'GET':
log.info('received GET to get files view')
if not u'form_type' in request.GET:
response_data = [{"error": _("Error when detecting form type, form_type is missing")}]
return HttpResponse(simplejson.dumps(response_data))
signer = Signer()
try:
form_type = signer.unsign(request.GET.get(u"form_type"))
except BadSignature:
response_data = [{"error": _("Tampering detected!")}]
return HttpResponse(simplejson.dumps(response_data))
#log.info('Got file: "%s"' % filename)
result = []
for p in request.GET.getlist(fieldname):
fl = MultiuploaderFile.objects.get(id=p)
thumb_url = ""
try:
thumb_url = get_thumbnail(fl.file, "80x80", quality=50)
except Exception as e:
log.error(e)
#generating json response array
result.append({"id": fl.id,
"name": fl.filename,
"size": fl.file.size,
"url": reverse('multiuploader_file_link', args=[fl.pk]),
"thumbnail_url": thumb_url,
"delete_url": reverse('multiuploader_delete', args=[fl.pk]),
"delete_type": "POST", })
response_data = simplejson.dumps(result)
#checking for json data type
#big thanks to Guy Shapiro
if noajax:
if request.META['HTTP_REFERER']:
redirect(request.META['HTTP_REFERER'])
if "application/json" in request.META['HTTP_ACCEPT_ENCODING']:
mimetype = 'application/json'
else:
mimetype = 'text/plain'
return HttpResponse(response_data, mimetype=mimetype)
else: # POST
return HttpResponse('Only GET accepted')
def multiuploader(request, noajax=False):
"""
Main Multiuploader module.
Parses data from jQuery plugin and makes database changes.
"""
if request.method == 'POST':
log.info('received POST to main multiuploader view')
if request.FILES is None:
response_data = [{"error": _('Must have files attached!')}]
return HttpResponse(simplejson.dumps(response_data))
if not u'form_type' in request.POST:
response_data = [{"error": _("Error when detecting form type, form_type is missing")}]
return HttpResponse(simplejson.dumps(response_data))
signer = Signer()
try:
form_type = signer.unsign(request.POST.get(u"form_type"))
except BadSignature:
response_data = [{"error": _("Tampering detected!")}]
return HttpResponse(simplejson.dumps(response_data))
form = MultiUploadForm(request.POST, request.FILES, form_type=form_type)
if not form.is_valid():
error = _("Unknown error")
if "file" in form._errors and len(form._errors["file"]) > 0:
error = form._errors["file"][0]
response_data = [{"error": error}]
return HttpResponse(simplejson.dumps(response_data))
file = request.FILES[u'file']
wrapped_file = UploadedFile(file)
filename = wrapped_file.name
file_size = wrapped_file.file.size
log.info('Got file: "%s"' % filename)
#writing file manually into model
#because we don't need form of any type.
fl = MultiuploaderFile()
fl.filename = filename
fl.file = file
fl.save()
log.info('File saving done')
thumb_url = ""
try:
thumb_url = get_thumbnail(fl.file, "80x80", quality=50)
except Exception as e:
log.error(e)
#generating json response array
result = [{"id": fl.id,
"name": filename,
"size": file_size,
"url": reverse('multiuploader_file_link', args=[fl.pk]),
"thumbnail_url": thumb_url,
"delete_url": reverse('multiuploader_delete', args=[fl.pk]),
"delete_type": "POST", }]
response_data = simplejson.dumps(result)
#checking for json data type
#big thanks to Guy Shapiro
if noajax:
if request.META['HTTP_REFERER']:
redirect(request.META['HTTP_REFERER'])
if "application/json" in request.META['HTTP_ACCEPT_ENCODING']:
mimetype = 'application/json'
else:
mimetype = 'text/plain'
return HttpResponse(response_data, mimetype=mimetype)
else: # GET
return HttpResponse('Only POST accepted')
def set_thumbnail(self, item, column):
self.current_thumbnail = QPixmap()
self.current_thumbnail.loadFromData(get_thumbnail(get_thumbnail_url(video=item.video)).read())
self.thumbnail_preview.setPixmap(self.current_thumbnail)
def compute_feats(bbdf):
X_pos = []
X_i = []
ids = []
file_counter = 1
prev_iid, prev_img = (None, None)
# FIXME, for debugging only! Reduced size or starting with offset
# bbdf = bbdf[28524:] # bbdf[54000:]
for n, row in tqdm(bbdf.iterrows(), total=len(bbdf)):
this_icorpus = row['i_corpus']
this_image_id = row['image_id']
this_region_id = row['region_id']
this_bb = row['bb']
# 2016-04-08: as note for future: When extracting
# feats for imagenet regions, must
# - create combined filename out of image_id and region_id
# - neutralise positional features, by setting bb given
# to it to 0,0,w,h. So that all ImageNet regions
# end up with same positions.
if code_icorpus[this_icorpus] == 'image_net':
this_image_id_mod = join_imagenet_id(this_image_id,
this_region_id)
this_bb_mod = [0,0,this_bb[2],this_bb[3]]
else:
this_image_id_mod = this_image_id
this_bb_mod = this_bb
if np.min(this_bb_mod[2:]) <= 0:
print 'skipping over this image (%s,%d). 0 bb! %s' % \
(code_icorpus[this_icorpus], this_image_id, str(this_bb_mod))
continue
(prev_iid, prev_img), img_resized = \
get_thumbnail((prev_iid, prev_img),
this_icorpus, this_image_id_mod, this_bb)
if len(prev_img.shape) != 3 or \
(len(prev_img.shape) == 3 and prev_img.shape[2] != 3):
print 'skipping over this image (%s,%d). b/w?' % \
(code_icorpus[this_icorpus], this_image_id)
continue
# If we continue below this line, getting region worked
X_i.append(img_resized)
this_pos_feats = compute_posfeats(prev_img, this_bb_mod)
X_pos.append(this_pos_feats)
ids.append(np.array([this_icorpus, this_image_id, this_region_id]))
# is it time to do the actual extraction on this batch
# and write out to disk?
if (n+1) % img_batch_size == 0:
filename = BASETEMPLATE_TMP % (code_icorpus[this_icorpus],
file_counter)
print strftime("%Y-%m-%d %H:%M:%S")
print "new batch!", n, file_counter, filename
try:
X = gltr.transform(X_i)
except ValueError as e:
print 'Exception! But why? Skipping this whole batch..'
X_i = []
ids = []
X_pos = []
continue
#raise e
X_ids = np.array(ids)
X_pos = np.array(X_pos)
print X_ids.shape, X.shape, X_pos.shape
X_f = np.hstack([X_ids,
X,
X_pos])
with gzip.open(filename, 'w') as f:
pickle.dump(X_f, f)
print X_f.shape
ids = []
X_pos = []
X_i = []
file_counter += 1
# and back to the for loop
# we're done, so what we have needs to be processed in any case
filename = BASETEMPLATE_TMP % (code_icorpus[this_icorpus],
file_counter)
print strftime("%Y-%m-%d %H:%M:%S")
print "final batch!", n, file_counter, filename
X = gltr.transform(X_i)
X_ids = np.array(ids)
X_pos = np.array(X_pos)
X_f = np.hstack([X_ids,
X,
X_pos])
with gzip.open(filename, 'w') as f:
pickle.dump(X_f, f)
print X_f.shape
def compute_feats(bbdf):
X_pos = []
X_i = []
ids = []
file_counter = 1
prev_iid, prev_img = (None, None)
# FIXME, for debugging only! Reduced size or starting with offset
# bbdf = bbdf[28524:] # bbdf[54000:]
for n, row in tqdm(bbdf.iterrows(), total=len(bbdf)):
this_icorpus = row['i_corpus']
this_image_id = row['image_id']
this_region_id = row['region_id']
this_bb = row['bb']
# 2016-04-08: as note for future: When extracting
# feats for imagenet regions, must
# - create combined filename out of image_id and region_id
# - neutralise positional features, by setting bb given
# to it to 0,0,w,h. So that all ImageNet regions
# end up with same positions.
if code_icorpus[this_icorpus] == 'image_net':
this_image_id_mod = join_imagenet_id(this_image_id, this_region_id)
this_bb_mod = [0, 0, this_bb[2], this_bb[3]]
else:
this_image_id_mod = this_image_id
this_bb_mod = this_bb
if np.min(this_bb_mod[2:]) <= 0:
print 'skipping over this image (%s,%d). 0 bb! %s' % \
(code_icorpus[this_icorpus], this_image_id, str(this_bb_mod))
continue
(prev_iid, prev_img), img_resized = \
get_thumbnail((prev_iid, prev_img),
this_icorpus, this_image_id_mod, this_bb)
if len(prev_img.shape) != 3 or \
(len(prev_img.shape) == 3 and prev_img.shape[2] != 3):
print 'skipping over this image (%s,%d). b/w?' % \
(code_icorpus[this_icorpus], this_image_id)
continue
# If we continue below this line, getting region worked
X_i.append(img_resized)
this_pos_feats = compute_posfeats(prev_img, this_bb_mod)
X_pos.append(this_pos_feats)
ids.append(np.array([this_icorpus, this_image_id, this_region_id]))
# is it time to do the actual extraction on this batch
# and write out to disk?
if (n + 1) % img_batch_size == 0:
filename = BASETEMPLATE_TMP % (code_icorpus[this_icorpus],
file_counter)
print strftime("%Y-%m-%d %H:%M:%S")
print "new batch!", n, file_counter, filename
try:
X = gltr.transform(X_i)
except ValueError as e:
print 'Exception! But why? Skipping this whole batch..'
X_i = []
ids = []
X_pos = []
continue
#raise e
X_ids = np.array(ids)
X_pos = np.array(X_pos)
print X_ids.shape, X.shape, X_pos.shape
X_f = np.hstack([X_ids, X, X_pos])
with gzip.open(filename, 'w') as f:
pickle.dump(X_f, f)
print X_f.shape
ids = []
X_pos = []
X_i = []
file_counter += 1
# and back to the for loop
# we're done, so what we have needs to be processed in any case
filename = BASETEMPLATE_TMP % (code_icorpus[this_icorpus], file_counter)
print strftime("%Y-%m-%d %H:%M:%S")
print "final batch!", n, file_counter, filename
X = gltr.transform(X_i)
X_ids = np.array(ids)
X_pos = np.array(X_pos)
X_f = np.hstack([X_ids, X, X_pos])
with gzip.open(filename, 'w') as f:
pickle.dump(X_f, f)
print X_f.shape
def serve_thumbnail(image):
print(f"Requested thumb {image}")
path, image = utils.get_thumbnail(image)
# return "Document not found!", 404
return send_from_directory(path, image)