def identify(self, request, *args, **kwargs):
"""Identify a photo."""
logging.debug("going to identify photo")
photo = self.get_object()
logging.debug("retrieved object")
# If the ROI is set, use that. If no ROI is set, then use the existing
# ROI if any. If the ROI is set, but evaluates to False, then set the
# ROI to None.
roi = request.data.get('roi', photo.roi)
if not roi:
roi = None
logging.debug("no ROI")
if photo.roi != roi:
photo.roi = roi
photo.save()
logging.debug("stored ROI")
# Set the ROI for the classifier.
if roi:
try:
roi = roi.split(',')
roi = [int(x) for x in roi]
assert len(roi) == 4
except:
return Response(
{'roi': "Must be of the format `x,y,width,height`"},
status=status.HTTP_400_BAD_REQUEST)
# Delete all photo identities, if any.
Identity.objects.filter(photo=photo).delete()
logging.debug("deleted photo identities")
# Classify the photo.
config = open_config(CONFIG_FILE)
logging.debug("read config file")
classifier = ImageClassifier(config)
logging.debug("instantiated ImageClassifier")
classifier.set_roi(roi)
logging.debug("applied ROI to ImageClassifier")
classes = classify_image(classifier, photo.image.path, ANN_DIR)
logging.debug("received classification")
# Identify this photo.
for c in classes:
if not c.get('genus'):
continue
id_ = Identity(photo=photo,
genus=c.get('genus'),
section=c.get('section'),
species=c.get('species'),
error=c.get('error'))
# Save the identity into the database.
id_.save()
return self.retrieve(request, *args, **kwargs)
def identify(self, request, *args, **kwargs):
"""Identify a photo."""
photo = self.get_object()
# If the ROI is set, use that. If no ROI is set, then use the existing
# ROI if any. If the ROI is set, but evaluates to False, then set the
# ROI to None.
roi = request.data.get('roi', photo.roi)
if not roi:
roi = None
if photo.roi != roi:
photo.roi = roi
photo.save()
# Set the ROI for the classifier.
if roi:
try:
roi = roi.split(',')
roi = [int(x) for x in roi]
assert len(roi) == 4
except:
return Response({'roi': "Must be of the format `x,y,width,height`"},
status=status.HTTP_400_BAD_REQUEST)
# Delete all photo identities, if any.
Identity.objects.filter(photo=photo).delete()
# Classify the photo.
config = open_config(CONFIG_FILE)
classifier = ImageClassifier(config)
classifier.set_roi(roi)
classes = classify_image(classifier, photo.image.path, ANN_DIR)
# Identify this photo.
for c in classes:
if not c.get('genus'):
continue
id_ = Identity(
photo=photo,
genus=c.get('genus'),
section=c.get('section'),
species=c.get('species'),
error=c.get('error')
)
# Save the identity into the database.
id_.save()
return self.retrieve(request, *args, **kwargs)
def test_trainer_ad(self):
"""Test the `classify` subcommands."""
filter_ = self.config.classification.filter.as_dict()
image = os.path.join(IMAGE_DIR,
"Cypripedium/Arietinum/plectrochilum/14990382409.jpg")
with db.session_scope(META_FILE) as (session, metadata):
classes = db.get_classes_from_filter(session, metadata, filter_)
if not classes:
raise ValueError("No classes found for filter `%s`" % filter_)
codewords = get_codewords(classes)
classifier = ImageClassifier(self.config)
codeword = classifier.classify_image(image, self.ann_file,
self.config)
classification = get_classification(codewords, codeword, 0.001)
class_ = [class_ for mse,class_ in classification]
print "Image is classified as {0}".format(", ".join(class_))
