def LoadDataset(filename, imagepath):
file_list = np.genfromtxt(filename, dtype=np.dtype([('Filename','S21'), ('Width', int), ('Height', int), ('roi_x1', int), ('roi_y1', int), ('roi_x2', int), ('roi_y2', int), ('classId', int)]))
ImageProcProxy.createCLAHE(clipLimit=1.4, tileGridSize=(2,2))
input_images = ImageProcProxy.emptyDataset(file_list.shape[0], params['input']['width'], params['input']['height'])
for sample in xrange(file_list.shape[0]):
image_file = ImageProcProxy.readImageColor(imagepath + file_list['Filename'][sample])
image_roi = ImageProcProxy.cropImage(image_file,
file_list['roi_x1'][sample], file_list['roi_y1'][sample],
file_list['roi_x2'][sample], file_list['roi_y2'][sample])
image_clahe = ImageProcProxy.emptyLike(image_roi)
image_clahe[:,:,0] = ImageProcProxy.applyCLAHE(image_roi[:,:,0])
image_clahe[:,:,1] = ImageProcProxy.applyCLAHE(image_roi[:,:,1])
image_clahe[:,:,2] = ImageProcProxy.applyCLAHE(image_roi[:,:,2])
image_resized = ImageProcProxy.resizeInterLinear(image_clahe,
params['input']['width'],
params['input']['height'])
image_gaussian = ImageProcProxy.applyGaussian(image_resized,
params['filter']['gaussian_radius'],
params['filter']['gaussian_sigma'])
image_int = ImageProcProxy.convertBGR2INT(image_gaussian)
image_vector = ImageProcProxy.flattenImage(image_int)
input_images[sample]= image_vector
return input_images, file_list['classId']
def LoadDataset(filename, imagepath):
file_list = np.genfromtxt(filename,
dtype=np.dtype([('Filename', 'S21'),
('Width', int), ('Height', int),
('roi_x1', int), ('roi_y1', int),
('roi_x2', int), ('roi_y2', int),
('classId', int)]))
ImageProcProxy.createCLAHE(clipLimit=1.4, tileGridSize=(2, 2))
input_images = ImageProcProxy.emptyDataset(file_list.shape[0],
params['input']['width'],
params['input']['height'])
for sample in xrange(file_list.shape[0]):
image_file = ImageProcProxy.readImageColor(
imagepath + file_list['Filename'][sample])
image_roi = ImageProcProxy.cropImage(image_file,
file_list['roi_x1'][sample],
file_list['roi_y1'][sample],
file_list['roi_x2'][sample],
file_list['roi_y2'][sample])
image_clahe = ImageProcProxy.emptyLike(image_roi)
image_clahe[:, :, 0] = ImageProcProxy.applyCLAHE(image_roi[:, :, 0])
image_clahe[:, :, 1] = ImageProcProxy.applyCLAHE(image_roi[:, :, 1])
image_clahe[:, :, 2] = ImageProcProxy.applyCLAHE(image_roi[:, :, 2])
image_resized = ImageProcProxy.resizeInterLinear(
image_clahe, params['input']['width'], params['input']['height'])
image_gaussian = ImageProcProxy.applyGaussian(
image_resized, params['filter']['gaussian_radius'],
params['filter']['gaussian_sigma'])
image_int = ImageProcProxy.convertBGR2INT(image_gaussian)
image_vector = ImageProcProxy.flattenImage(image_int)
input_images[sample] = image_vector
return input_images, file_list['classId']
