def generate_hog_gabor_subfolders(folder, folder2=None, label=0):
tao = 4.
elongation = 8.
sigmax = tao / 2.35
sigmay = sigmax * elongation
from src.utils.features import HOG
from src.utils.gabor import gabor_feature_real
from src.utils.io import filename2arr
X = []
Y = []
for dirName, subdirList, fileList in os.walk(folder):
for subdir in subdirList:
for dirName2, subdirList2, fileList in os.walk(dirName + '/' +subdir):
for filename in fileList:
parts = filename.split('.')
if parts[0] == '':
continue
print "generating file " + dirName2 + '/'+ filename
arr = filename2arr(dirName2 + '/' + filename)
_, max_magnitude, _ = gabor_feature_real(arr, sigmax=sigmax, sigmay=sigmay)
from src.utils.gabor import normalize
ng = normalize(max_magnitude).reshape(1, -1)
arr2 = filename2arr(folder2 + '/' + subdir + '/' + filename)
fd = HOG(arr2).reshape(1, -1)
feature = np.concatenate((ng, fd), axis=1)
X.append(feature)
Y.append(label)
return X, Y
def generate_hog_negative_fixed(folder):
from src.utils.features import HOG
from src.utils.io import filename2arr
X = []
Y = []
for dirName, subdirList, fileList in os.walk(folder):
for filename in fileList:
parts = filename.split('.')
if parts[0] == '':
continue
print "generating file " + dirName + '/' + filename
arr = filename2arr(dirName + '/' + filename)
fd = HOG(arr)
X.append(fd)
Y.append(0)
return X, Y
def generate_hog_negative(folder, winW=400, winH=400):
from src.utils.features import HOG
from src.utils.io import filename2arr
from src.utils.util import sliding_window
X = []
Y = []
for dirName, subdirList, fileList in os.walk(folder):
for filename in fileList:
parts = filename.split('.')
if parts[0] == '':
continue
print "generating file " + dirName + '/' + filename
arr_big = filename2arr(dirName + '/' + filename)
for (arr, m, n) in sliding_window(arr_big, winW=winW, winH=winH):
fd = HOG(arr)
X.append(fd)
Y.append(0)
return X, Y
def generate_blur_canny_subfolders(folder, outputFolder):
from src.utils.canny import my_canny
from src.utils.canny import best_edges
from src.utils.io import filename2arr
from src.utils.io import saveimage_pil
import os
for dirName, subdirList, fileList in os.walk(folder):
for subdir in subdirList:
for dirName2, subdirList2, fileList in os.walk(dirName + '/' +subdir):
for filename in fileList:
parts = filename.split('.')
if parts[0] == '':
continue
arr = filename2arr(dirName2 + '/' + filename)
ret = best_edges(arr)
if not os.path.exists(outputFolder + '/' + subdir):
os.makedirs(outputFolder + '/' + subdir)
outfn = outputFolder + '/' + subdir + '/'+ parts[0] + '.jpg'
print "saving canny file " + outfn
saveimage_pil(255 * ret.astype('uint8'), outfn, show=False)
data_folder = xray_dir + '/data/LL/' result_folder = '/Users/ruhansa/Desktop/train/result/' winH=400 winW=400 step_size_W = 30 step_size_H = 30 testn = '1' clfn = 'clf_1_2' """ ############################### initial box load ############################### """ fn = data_folder + testn + '.jpg' arr = filename2arr(fn) img = Image.fromarray(arr) windows = [] fn = result_folder + testn + '_' + clfn + '/boxes.pkl' boxes = pickle.load(open(fn, "rb")) """ ############################### detect edges based on boxes, preprocess if necessary. ############################### """ # from src.utils.canny import my_canny # from src.utils.preprocessing import normalize # box = boxes[2] # window = arr[box[1]: box[3], box[0]: box[2]] # to eliminate the edge scenario # img = Image.fromarray(window)
set env path ############################### """ src_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) # script directory src/ xray_dir = os.path.dirname(src_dir) # xray directory os.chdir(xray_dir) sys.path.append(src_dir) """ ################################### set input/output path and read data ################################### """ filenum = "1" targetfn = xray_dir + "/data/LL/" + filenum + ".jpg" target_arr = filename2arr(targetfn) # TODO: crop up ROI from target_arr filenum = "1" modelfn = xray_dir + "/data/train/L3/" + filenum + ".jpg" model_arr = filename2arr(modelfn) """ ################################### preprocessing ################################### """ from src.utils.preprocessing import preprocessing target = preprocessing(target_arr) model = preprocessing(model_arr)
import os import sys import inspect from src.utils.io import filename2arr """ ############################### set env path ############################### """ tests_dir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe()))) # script directory src/ src_dir = os.path.dirname(tests_dir) xray_dir = os.path.dirname(src_dir) #xray directory os.chdir(xray_dir) sys.path.append(src_dir) filenum = '1' targetfn = xray_dir+ '/data/LL/' + filenum + '.jpg' target_arr = filename2arr(targetfn) from src.utils.preprocessing import preprocessing target = preprocessing(target_arr) from src.utils.features import sift_descriptor t_kp, t_des = sift_descriptor(target,show=True)