def run_roi(self):
# Just runs the latest ROI for now
rbc_seg.segmentation(self.roi_list[len(self.roi_list)-1][1])
labels_smeared = [3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3,3]
#labels1 = [2,2,3,0,1,2,2,2,1,1,1,3,0,2,0,2,3,0,1,1, 0,0,1,1,0,1,0,1,3,3]
labels1 = [2,2,3,0,1,2,2,1,1,0,0,2,0,2,3,0,1,1,0,0,1,1,0,1,0,1,0,3,2,1]
labels_1_hard = [2,1,0,0,1,0,2,2,1,2,1,3,2,2,1,1,1,2,2,0,0,2,0,2,0,2,2,2,0,0]
labels_crap_1 = [3 for i in range(73)]
print "alla:", len(labels_crap_1) + len(labels1) + len(labels_1_hard) + len(labels2) + len(labels_smeared)
#labels_others_1 = [3 for i in range(len(cell_list_others_1))]
all_labels = [labels1, labels2, labels_1_hard, labels_smeared, labels_crap_1]
labels = []
for i,filename in enumerate(training_files):
testimg = cv2.imread("../npyimages/" + filename)
testimg = cv2.cvtColor(testimg, cv2.COLOR_BGR2RGB)
if filename == "only_whites_clean.png":
cell_list = rbc_seg.segmentation(testimg)
del cell_list[11]
del cell_list[7]
print "len clean:", len(cell_list)
elif filename == "only_whites_1_hard.png":
cell_list_1_hard_ = rbc_seg.segmentation(testimg)
cell_list = []
cell_list.append(cell_list_1_hard_[8])
cell_list.append(cell_list_1_hard_[10])
cell_list.append(cell_list_1_hard_[16])
cell_list.append(cell_list_1_hard_[23])
cell_list.append(cell_list_1_hard_[32])
cell_list.append(cell_list_1_hard_[47])
cell_list.append(cell_list_1_hard_[59])
cell_list.append(cell_list_1_hard_[62])
