class vis_tool:
def __init__(self):
self.args = parse_args()
cfg = mmcv.Config.fromfile(self.args.config)
self.window = Tk()
self.menubar = Menu(self.window)
self.info = StringVar()
self.info_label = Label(
self.window, bg='yellow', width=4, textvariable=self.info)
self.listBox_img = Listbox(
self.window, width=50, height=25, font=('Times New Roman', 10))
self.listBox_obj = Listbox(
self.window, width=50, height=12, font=('Times New Roman', 10))
self.scrollbar_img = Scrollbar(
self.window, width=15, orient='vertical')
self.scrollbar_obj = Scrollbar(
self.window, width=15, orient='vertical')
self.listBox_img_info = StringVar()
self.listBox_img_label = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=4,
height=1,
textvariable=self.listBox_img_info)
self.listBox_obj_info = StringVar()
self.listBox_obj_label1 = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=4,
height=1,
textvariable=self.listBox_obj_info)
self.listBox_obj_label2 = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=4,
height=1,
text='Object Class : Score (IoU)')
if cfg.dataset_type == 'VOCDataset':
self.data_info = VOC_dataset(cfg, self.args)
elif cfg.dataset_type == 'CocoDataset':
self.data_info = COCO_dataset(cfg, self.args)
self.info.set('DATASET: {}'.format(self.data_info.dataset))
# load image and show it on the window
self.img = self.data_info.get_img_by_index(0)
self.photo = ImageTk.PhotoImage(self.img)
self.label_img = Label(self.window, image=self.photo)
self.show_det_txt = IntVar(value=1)
self.checkbn_det_txt = Checkbutton(
self.window,
text='Text',
font=('Arial', 10, 'bold'),
variable=self.show_det_txt,
command=self.change_img,
fg='#0000FF')
self.show_dets = IntVar(value=1)
self.checkbn_det = Checkbutton(
self.window,
text='Detections',
font=('Arial', 10, 'bold'),
variable=self.show_dets,
command=self.change_img,
fg='#0000FF')
self.show_gt_txt = IntVar(value=1)
self.checkbn_gt_txt = Checkbutton(
self.window,
text='Text',
font=('Arial', 10, 'bold'),
variable=self.show_gt_txt,
command=self.change_img,
fg='#FF8C00')
self.show_gts = IntVar(value=1)
self.checkbn_gt = Checkbutton(
self.window,
text='Groundtruth',
font=('Arial', 10, 'bold'),
variable=self.show_gts,
command=self.change_img,
fg='#FF8C00')
self.combo_label = Label(
self.window,
bg='yellow',
width=10,
height=1,
text='Show Category',
font=('Arial', 11))
self.combo_category = ttk.Combobox(
self.window,
font=('Arial', 11),
values=self.data_info.aug_category.combo_list)
self.combo_category.current(0)
self.th_label = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=10,
height=1,
text='Score Threshold')
self.threshold = np.float32(0.5)
self.th_entry = Entry(
self.window,
font=('Arial', 11),
width=10,
textvariable=StringVar(self.window, value=str(self.threshold)))
self.th_button = Button(
self.window, text='Enter', height=1, command=self.change_threshold)
self.iou_th_label = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=10,
height=1,
text='IoU Threshold')
self.iou_threshold = np.float32(0.5)
self.iou_th_entry = Entry(
self.window,
font=('Arial', 11),
width=10,
textvariable=StringVar(self.window, value=str(self.iou_threshold)))
self.iou_th_button = Button(
self.window, text='Enter', height=1, command=self.change_iou_threshold)
self.find_label = Label(
self.window,
font=('Arial', 11),
bg='yellow',
width=10,
height=1,
text='find')
self.find_name = ''
self.find_entry = Entry(
self.window,
font=('Arial', 11),
width=10,
textvariable=StringVar(self.window, value=str(self.find_name)))
self.find_button = Button(
self.window, text='Enter', height=1, command=self.findname)
self.listBox_img_idx = 0
# ====== ohter attribute ======
self.img_name = ''
self.show_img = None
self.output = self.args.output
if not os.path.isdir(self.output):
os.makedirs(self.output)
self.img_list = self.data_info.img_list
# flag for find/threshold button switch focused element
self.button_clicked = False
def change_threshold(self, event=None):
try:
self.threshold = np.float32(self.th_entry.get())
self.change_img()
# after changing threshold, focus on listBox for easy control
if self.window.focus_get() == self.listBox_obj:
self.listBox_obj.focus()
else:
self.listBox_img.focus()
self.button_clicked = True
except ValueError:
self.window.title('Please enter a number as score threshold.')
def change_iou_threshold(self, event=None):
try:
self.iou_threshold = np.float32(self.iou_th_entry.get())
self.change_img()
# after changing threshold, focus on listBox for easy control
if self.window.focus_get() == self.listBox_obj:
self.listBox_obj.focus()
else:
self.listBox_img.focus()
self.button_clicked = True
except ValueError:
self.window.title("Please enter a number as IoU threshold.")
# draw groundtruth
def draw_gt_boxes(self, img, objs):
for obj in objs:
cls_name = obj[0]
# according combobox to decide whether to plot this category
if self.combo_category.get() == 'All':
show_category = self.data_info.aug_category.category
else:
show_category = [self.combo_category.get()]
if cls_name not in show_category:
continue
box = obj[1:]
xmin = max(box[0], 0)
ymin = max(box[1], 0)
xmax = min(box[0] + box[2], self.img_width)
ymax = min(box[1] + box[3], self.img_height)
font = cv2.FONT_HERSHEY_SIMPLEX
if self.show_gt_txt.get():
if ymax + 30 >= self.img_height:
cv2.rectangle(img, (xmin, ymin),
(xmin + len(cls_name) * 10, int(ymin - 20)),
(255, 140, 0), cv2.FILLED)
cv2.putText(img, cls_name, (xmin, int(ymin - 5)), font,
0.5, (255, 255, 255), 1)
else:
cv2.rectangle(img, (xmin, ymax),
(xmin + len(cls_name) * 10, int(ymax + 20)),
(255, 140, 0), cv2.FILLED)
cv2.putText(img, cls_name, (xmin, int(ymax + 15)), font,
0.5, (255, 255, 255), 1)
cv2.rectangle(img, (xmin, ymin), (xmax, ymax),
self.args.gt_box_color, 1)
return img
def get_iou(self, det):
iou = np.zeros_like(det)
GT = self.data_info.get_singleImg_gt(self.img_name)
for idx, cls_objs in enumerate(det):
category = self.data_info.aug_category.category[idx]
BBGT = []
for t in GT:
if not t[0] == category: continue
BBGT.append([t[1], t[2], t[1] + t[3], t[2] + t[4]])
BBGT = np.asarray(BBGT)
d = [0] * len(BBGT) # for check 1 GT map to several det
confidence = cls_objs[:, 4]
BB = cls_objs[:, 0:4] # bounding box
# sort by confidence
sorted_ind = np.argsort(-confidence)
sorted_scores = np.sort(-confidence)
BB = BB[sorted_ind, :]
# for returning original order
ind_table = {i: sorted_ind[i] for i in range(len(sorted_ind))}
iou[idx] = np.zeros(len(BB))
if len(BBGT) > 0:
for i in range(len(BB)):
bb = BB[i, :]
# compute overlaps
# intersection
ixmin = np.maximum(BBGT[:, 0], bb[0])
iymin = np.maximum(BBGT[:, 1], bb[1])
ixmax = np.minimum(BBGT[:, 2], bb[2])
iymax = np.minimum(BBGT[:, 3], bb[3])
iw = np.maximum(ixmax - ixmin + 1., 0.)
ih = np.maximum(iymax - iymin + 1., 0.)
inters = iw * ih
# union
uni = ((bb[2] - bb[0] + 1.) * (bb[3] - bb[1] + 1.) +
(BBGT[:, 2] - BBGT[:, 0] + 1.) * (BBGT[:, 3] - BBGT[:, 1] + 1.) -
inters)
overlaps = inters / uni
ovmax = np.max(overlaps) # max overlaps with all gt
jmax = np.argmax(overlaps)
if ovmax > self.iou_threshold:
if not d[jmax]:
d[jmax] = 1
else: # multiple bounding boxes map to one gt
ovmax = -ovmax
iou[idx][ind_table[i]] = ovmax # return to unsorted order
return iou
def draw_all_det_boxes(self, img, single_detection):
if self.data_info.has_anno:
self.iou = self.get_iou(single_detection)
for idx, cls_objs in enumerate(single_detection):
category = self.data_info.aug_category.category[idx]
if self.combo_category.get() == 'All':
show_category = self.data_info.aug_category.category
else:
show_category = [self.combo_category.get()]
if category not in show_category:
continue
for obj_idx, obj in enumerate(cls_objs):
[score, box] = [round(obj[4], 2), obj[:4]]
if score >= self.threshold:
box = list(map(int, list(map(round, box))))
xmin = max(box[0], 0)
ymin = max(box[1], 0)
xmax = min(box[2], self.img_width)
ymax = min(box[3], self.img_height)
if not self.data_info.has_anno or \
self.iou[idx][obj_idx] >= self.iou_threshold:
color = self.args.det_box_color
else:
color = (255, 0, 0)
if self.show_det_txt.get():
font = cv2.FONT_HERSHEY_SIMPLEX
text = category + ' : ' + str(score)
if ymax + 30 >= self.img_height:
cv2.rectangle(
img, (xmin, ymin),
(xmin + len(text) * 9, int(ymin - 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymin - 5)), font,
0.5, (255, 255, 255), 1)
else:
cv2.rectangle(
img, (xmin, ymax),
(xmin + len(text) * 9, int(ymax + 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymax + 15)),
font, 0.5, (255, 255, 255), 1)
cv2.rectangle(img, (xmin, ymin), (xmax, ymax), color, 2)
return img
def draw_all_det_boxes_masks(self, img, single_detection):
img = np.require(img, requirements=['W'])
boxes, masks = single_detection
# draw segmentation masks
# reference mmdetection/mmdet/models/detectors/base.py
if self.combo_category.get() != 'All':
show_idx = self.data_info.aug_category.category.index(
self.combo_category.get())
masks = np.asarray([masks[show_idx]])
boxes = np.asarray([boxes[show_idx]])
category = self.data_info.aug_category.category[show_idx]
segms = list(itertools.chain(*masks))
bboxes = np.vstack(boxes)
inds = np.where(np.round(bboxes[:, -1], 2) >= self.threshold)[0]
self.color_list = []
for i in inds:
color_mask = np.random.randint(0, 256, (1, 3), dtype=np.uint8)
mask = maskUtils.decode(segms[i]).astype(np.bool)
img[mask] = img[mask] * 0.5 + color_mask * 0.5
self.color_list.append('#%02x%02x%02x' % tuple(color_mask[0]))
if self.data_info.has_anno:
boxes2, _ = single_detection
self.iou = self.get_iou(boxes2)
if self.combo_category.get() != 'All':
iou = np.asarray([self.iou[show_idx]])
else:
iou = self.iou
# draw bounding box
for idx, cls_objs in enumerate(boxes):
if self.combo_category.get() == 'All':
category = self.data_info.aug_category.category[idx]
for obj_idx, obj in enumerate(cls_objs):
[score, box] = [round(obj[4], 2), obj[:4]]
if score >= self.threshold:
box = list(map(int, list(map(round, box))))
xmin = max(box[0], 0)
ymin = max(box[1], 0)
xmax = min(box[2], self.img_width)
ymax = min(box[3], self.img_height)
if not self.data_info.has_anno or \
iou[idx][obj_idx] >= self.iou_threshold:
color = self.args.det_box_color
else:
color = (255, 0, 0)
if self.show_det_txt.get():
font = cv2.FONT_HERSHEY_SIMPLEX
text = category + ' : ' + str(score)
if ymax + 30 >= self.img_height:
cv2.rectangle(
img, (xmin, ymin),
(xmin + len(text) * 9, int(ymin - 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymin - 5)), font,
0.5, (255, 255, 255), 1)
else:
cv2.rectangle(
img, (xmin, ymax),
(xmin + len(text) * 9, int(ymax + 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymax + 15)),
font, 0.5, (255, 255, 255), 1)
cv2.rectangle(img, (xmin, ymin), (xmax, ymax), color, 2)
return img
def change_img(self, event=None):
if len(self.listBox_img.curselection()) != 0:
self.listBox_img_idx = self.listBox_img.curselection()[0]
self.listBox_img_info.set('Image {:6} / {:6}'.format(
self.listBox_img_idx + 1, self.listBox_img.size()))
name = self.listBox_img.get(self.listBox_img_idx)
self.window.title('DATASET : ' + self.data_info.dataset + ' ' + name)
img = self.data_info.get_img_by_name(name)
self.img_width, self.img_height = img.width, img.height
img = np.asarray(img)
self.img_name = name
self.img = img
if self.data_info.has_anno and self.show_gts.get():
objs = self.data_info.get_singleImg_gt(name)
img = self.draw_gt_boxes(img, objs)
if self.data_info.results is not None and self.show_dets.get():
if self.data_info.mask is False:
dets = self.data_info.get_singleImg_dets(name)
img = self.draw_all_det_boxes(img, dets)
else:
dets = self.data_info.get_singleImg_dets(name).transpose(
(1, 0))
img = self.draw_all_det_boxes_masks(img, dets)
self.clear_add_listBox_obj()
self.show_img = img
img = Image.fromarray(img)
img = self.scale_img(img)
self.photo = ImageTk.PhotoImage(img)
self.label_img.config(image=self.photo)
self.window.update_idletasks()
if self.img_name in os.listdir(self.output):
self.listBox_img_label.config(bg='#CCFF99')
else:
self.listBox_img_label.config(bg='yellow')
def draw_one_det_boxes(self, img, single_detection, selected_idx=-1):
idx_counter = 0
for idx, cls_objs in enumerate(single_detection):
category = self.data_info.aug_category.category[idx]
if self.combo_category.get() == 'All':
show_category = self.data_info.aug_category.category
else:
show_category = [self.combo_category.get()]
if category not in show_category:
continue
for obj_idx, obj in enumerate(cls_objs):
[score, box] = [round(obj[4], 2), obj[:4]]
if score >= self.threshold:
if idx_counter == selected_idx:
box = list(map(int, list(map(round, box))))
xmin = max(box[0], 0)
ymin = max(box[1], 0)
xmax = min(box[2], self.img_width)
ymax = min(box[3], self.img_height)
if not self.data_info.has_anno or \
self.iou[idx][obj_idx] >= self.iou_threshold:
color = self.args.det_box_color
else:
color = (255, 0, 0)
if self.show_det_txt.get():
font = cv2.FONT_HERSHEY_SIMPLEX
text = category + ' : ' + str(score)
if ymax + 30 >= self.img_height:
cv2.rectangle(
img, (xmin, ymin),
(xmin + len(text) * 9, int(ymin - 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymin - 5)),
font, 0.5, (255, 255, 255), 1)
else:
cv2.rectangle(
img, (xmin, ymax),
(xmin + len(text) * 9, int(ymax + 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymax + 15)),
font, 0.5, (255, 255, 255), 1)
cv2.rectangle(img, (xmin, ymin), (xmax, ymax), color, 2)
return img
else:
idx_counter += 1
def draw_one_det_boxes_masks(self, img, single_detection, selected_idx=-1):
img = np.require(img, requirements=['W'])
boxes, masks = single_detection
# draw segmentation masks
# reference mmdetection/mmdet/models/detectors/base.py
if self.combo_category.get() != 'All':
show_idx = self.data_info.aug_category.category.index(
self.combo_category.get())
category = self.data_info.aug_category.category[
show_idx] # fixed category
masks = np.asarray([masks[show_idx]])
boxes = np.asarray([boxes[show_idx]])
segms = list(itertools.chain(*masks))
bboxes = np.vstack(boxes)
inds = np.where(np.round(bboxes[:, -1], 2) >= self.threshold)[0]
self.color_list = []
for inds_idx, i in enumerate(inds):
if inds_idx == selected_idx:
color_mask = np.random.randint(0, 256, (1, 3), dtype=np.uint8)
mask = maskUtils.decode(segms[i]).astype(np.bool)
img[mask] = img[mask] * 0.5 + color_mask * 0.5
self.color_list.append('#%02x%02x%02x' % tuple(color_mask[0]))
if self.data_info.has_anno:
if self.combo_category.get() != 'All':
iou = np.asarray([self.iou[show_idx]])
else:
iou = self.iou
# draw bounding box
idx_counter = 0
for idx, cls_objs in enumerate(boxes):
if self.combo_category.get() == 'All':
category = self.data_info.aug_category.category[idx]
for obj_idx, obj in enumerate(cls_objs):
[score, box] = [round(obj[4], 2), obj[:4]]
if score >= self.threshold:
if idx_counter == selected_idx:
box = list(map(int, list(map(round, box))))
xmin = max(box[0], 0)
ymin = max(box[1], 0)
xmax = min(box[2], self.img_width)
ymax = min(box[3], self.img_height)
if not self.data_info.has_anno or \
iou[idx][obj_idx] >= self.iou_threshold:
color = self.args.det_box_color
else:
color = (255, 0, 0)
if self.show_det_txt.get():
font = cv2.FONT_HERSHEY_SIMPLEX
text = category + ' : ' + str(score)
if ymax + 30 >= self.img_height:
cv2.rectangle(
img, (xmin, ymin),
(xmin + len(text) * 9, int(ymin - 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymin - 5)),
font, 0.5, (255, 255, 255), 1)
else:
cv2.rectangle(
img, (xmin, ymax),
(xmin + len(text) * 9, int(ymax + 20)),
(0, 0, 255), cv2.FILLED)
cv2.putText(img, text, (xmin, int(ymax + 15)),
font, 0.5, (255, 255, 255), 1)
cv2.rectangle(img, (xmin, ymin), (xmax, ymax),
color, 2)
return img
else:
idx_counter += 1
# plot only one object
def change_obj(self, event=None):
if len(self.listBox_obj.curselection()) == 0:
self.listBox_img.focus()
return
else:
listBox_obj_idx = self.listBox_obj.curselection()[0]
self.listBox_obj_info.set('Detected Object : {:4} / {:4}'.format(
listBox_obj_idx + 1, self.listBox_obj.size()))
name = self.listBox_img.get(self.listBox_img_idx)
img = self.data_info.get_img_by_name(name)
self.img_width, self.img_height = img.width, img.height
img = np.asarray(img)
self.img_name = name
self.img = img
if self.data_info.has_anno and self.show_gts.get():
objs = self.data_info.get_singleImg_gt(name)
img = self.draw_gt_boxes(img, objs)
if self.data_info.results is not None and self.show_dets.get():
if self.data_info.mask is False:
dets = self.data_info.get_singleImg_dets(name)
img = self.draw_one_det_boxes(img, dets, listBox_obj_idx)
else:
dets = self.data_info.get_singleImg_dets(name).transpose(
(1, 0))
img = self.draw_one_det_boxes_masks(img, dets, listBox_obj_idx)
self.show_img = img
img = Image.fromarray(img)
img = self.scale_img(img)
self.photo = ImageTk.PhotoImage(img)
self.label_img.config(image=self.photo)
self.window.update_idletasks()
if self.img_name in os.listdir(self.output):
self.listBox_img_label.config(bg='#CCFF99')
else:
self.listBox_img_label.config(bg='yellow')
# ============================================
def scale_img(self, img):
[s_w, s_h] = [1, 1]
# if window size is (1920, 1080),
# the default max image size is (1440, 810)
(fix_width, fix_height) = (1440, 810)
# change image size according to window size
if self.window.winfo_width() != 1:
fix_width = (
self.window.winfo_width() - self.listBox_img.winfo_width() -
self.scrollbar_img.winfo_width() - 5)
# fix_height = int(fix_width * 9 / 16)
fix_height = 750
# handle image size is too big
if img.width > fix_width:
s_w = fix_width / img.width
if img.height > fix_height:
s_h = fix_height / img.height
scale = min(s_w, s_h)
img = img.resize((int(img.width * scale), int(img.height * scale)),
Image.ANTIALIAS)
return img
def clear_add_listBox_obj(self):
self.listBox_obj.delete(0, 'end')
if self.data_info.mask is False:
single_detection = self.data_info.get_singleImg_dets(
self.img_list[self.listBox_img_idx])
else:
single_detection, single_mask = self.data_info.get_singleImg_dets(
self.img_list[self.listBox_img_idx]).transpose((1, 0))
if self.combo_category.get() == 'All':
show_category = self.data_info.aug_category.category
else:
show_category = [self.combo_category.get()]
num = 0
for idx, cls_objs in enumerate(single_detection):
category = self.data_info.aug_category.category[idx]
if category not in show_category:
continue
for obj_idx, obj in enumerate(cls_objs):
score = np.round(obj[4], 2)
if score >= self.threshold:
if not self.data_info.has_anno:
self.listBox_obj.insert('end',
category + " : " + str(score))
elif self.iou[idx][obj_idx] > self.iou_threshold:
s = "{:15} : {:5.3} ( {:<6.3})".format(
category, score, abs(round(self.iou[idx][obj_idx], 2)))
self.listBox_obj.insert('end', s)
self.listBox_obj.itemconfig(num, fg="green")
else:
s = "{:15} : {:5.3} ( {:<6.3})".format(
category, score, abs(round(self.iou[idx][obj_idx], 2)))
self.listBox_obj.insert('end', s)
self.listBox_obj.itemconfig(num, fg="red")
num += 1
self.listBox_obj_info.set('Detected Object : {:3}'.format(num))
def change_threshold_button(self, v):
self.threshold += v
if self.threshold <= 0:
self.threshold = 0
elif self.threshold >= 1:
self.threshold = 1
self.th_entry.delete(0, END)
self.th_entry.insert(0, str(round(self.threshold, 2)))
self.change_threshold()
def change_iou_threshold_button(self, v):
self.iou_threshold += v
if self.iou_threshold <= 0:
self.iou_threshold = 0
elif self.iou_threshold >= 1:
self.iou_threshold = 1
self.iou_th_entry.delete(0, END)
self.iou_th_entry.insert(0, str(round(self.iou_threshold, 2)))
self.change_iou_threshold()
def save_img(self):
print('Save image to ' + os.path.join(self.output, self.img_name))
cv2.imwrite(
os.path.join(self.output, self.img_name),
cv2.cvtColor(self.show_img, cv2.COLOR_BGR2RGB))
self.listBox_img_label.config(bg='#CCFF99')
def eventhandler(self, event):
entry_list = [self.find_entry, self.th_entry, self.iou_th_entry]
if self.window.focus_get() not in entry_list:
if platform.system() == 'Windows':
state_1key = 8
state_2key = 12
else: # 'Linux'
state_1key = 16
state_2key = 20
if event.state == state_2key and event.keysym == 'Left':
self.change_iou_threshold_button(-0.1)
elif event.state == state_2key and event.keysym == 'Right':
self.change_iou_threshold_button(0.1)
elif event.state == state_1key and event.keysym == 'Left':
self.change_threshold_button(-0.1)
elif event.state == state_1key and event.keysym == 'Right':
self.change_threshold_button(0.1)
elif event.keysym == 'q':
self.window.quit()
elif event.keysym == 's':
self.save_img()
if self.button_clicked:
self.button_clicked = False
else:
if event.keysym in ['KP_Enter', 'Return']:
self.listBox_obj.focus()
self.listBox_obj.select_set(0)
elif event.keysym == 'Escape':
self.change_img()
self.listBox_img.focus()
def combobox_change(self, event=None):
self.listBox_img.focus()
self.change_img()
def clear_add_listBox_img(self):
self.listBox_img.delete(0, 'end') # delete listBox_img 0 ~ end items
# add image name to listBox_img
for item in self.img_list:
self.listBox_img.insert('end', item)
self.listBox_img.select_set(0)
self.listBox_img.focus()
self.change_img()
def findname(self, event=None):
self.find_name = self.find_entry.get()
new_list = []
if self.find_name == '':
new_list = self.data_info.img_list
else:
for img_name in self.data_info.img_list:
if self.find_name[0] == '!':
if self.find_name[1:] not in img_name:
new_list.append(img_name)
else:
if self.find_name in img_name:
new_list.append(img_name)
if len(new_list) != 0:
self.img_list = new_list
self.clear_add_listBox_img()
self.clear_add_listBox_obj()
self.button_clicked = True
else:
self.window.title("Can't find any image about '{}'".format(
self.find_name))
def run(self):
self.window.title('DATASET : ' + self.data_info.dataset)
self.window.geometry('1280x800+350+100')
# self.menubar.add_command(label='QUIT', command=self.window.quit)
self.window.config(menu=self.menubar) # display the menu
self.scrollbar_img.config(command=self.listBox_img.yview)
self.listBox_img.config(yscrollcommand=self.scrollbar_img.set)
self.scrollbar_obj.config(command=self.listBox_obj.yview)
self.listBox_obj.config(yscrollcommand=self.scrollbar_obj.set)
layer1 = 0
layer2 = 50
# ======================= layer 1 =========================
# combobox
self.combo_label.grid(
row=layer1 + 30,
column=0,
sticky=W + E + N + S,
padx=3,
pady=3,
columnspan=6)
self.combo_category.grid(
row=layer1 + 30,
column=6,
sticky=W + E + N + S,
padx=3,
pady=3,
columnspan=6)
# show det
self.checkbn_det.grid(
row=layer1 + 40,
column=0,
sticky=N + S,
padx=3,
pady=3,
columnspan=4)
# show det text
self.checkbn_det_txt.grid(
row=layer1 + 40,
column=4,
sticky=N + S,
padx=3,
pady=3,
columnspan=2)
if self.data_info.has_anno != False:
# show gt
self.checkbn_gt.grid(
row=layer1 + 40,
column=6,
sticky=N + S,
padx=3,
pady=3,
columnspan=4)
# show gt text
self.checkbn_gt_txt.grid(
row=layer1 + 40,
column=10,
sticky=N + S,
padx=3,
pady=3,
columnspan=2)
# ======================= layer 2 =========================
self.listBox_img_label.grid(
row=layer2 + 0, column=0, sticky=N + S + E + W, columnspan=12)
# find name
self.find_label.grid(
row=layer2 + 20, column=0, sticky=E + W, columnspan=4)
self.find_entry.grid(
row=layer2 + 20, column=4, sticky=E + W, columnspan=4)
self.find_button.grid(
row=layer2 + 20, column=8, sticky=E + W, pady=3, columnspan=4)
self.scrollbar_img.grid(row=layer2 + 30, column=11, sticky=N + S + W)
self.label_img.grid(
row=layer1 + 30,
column=12,
sticky=N + E,
padx=3,
pady=3,
rowspan=110)
self.listBox_img.grid(
row=layer2 + 30,
column=0,
sticky=N + S + E + W,
pady=3,
columnspan=11)
if self.data_info.det_file != '':
self.th_label.grid(
row=layer2 + 40, column=0, sticky=E + W, columnspan=6)
self.th_entry.grid(
row=layer2 + 40, column=6, sticky=E + W, columnspan=3)
self.th_button.grid(
row=layer2 + 40, column=9, sticky=E + W, columnspan=3)
if self.data_info.has_anno != False:
self.iou_th_label.grid(
row=layer2 + 50, column=0, sticky=E + W, columnspan=6)
self.iou_th_entry.grid(
row=layer2 + 50, column=6, sticky=E + W, columnspan=3)
self.iou_th_button.grid(
row=layer2 + 50, column=9, sticky=E + W, columnspan=3)
self.listBox_obj_label1.grid(
row=layer2 + 60, column=0, sticky=E + W, pady=3, columnspan=12)
if self.data_info.has_anno != False:
self.listBox_obj_label2.grid(
row=layer2 + 70,
column=0,
sticky=E + W,
pady=2,
columnspan=12)
self.scrollbar_obj.grid(
row=layer2 + 80, column=11, sticky=N + S + W, pady=3)
self.listBox_obj.grid(
row=layer2 + 80,
column=0,
sticky=N + S + E + W,
pady=3,
columnspan=11)
self.clear_add_listBox_img()
self.listBox_img.bind('<<ListboxSelect>>', self.change_img)
self.listBox_img.bind_all('<KeyRelease>', self.eventhandler)
self.listBox_obj.bind('<<ListboxSelect>>', self.change_obj)
self.th_entry.bind('<Return>', self.change_threshold)
self.th_entry.bind('<KP_Enter>', self.change_threshold)
self.iou_th_entry.bind('<Return>', self.change_iou_threshold)
self.iou_th_entry.bind('<KP_Enter>', self.change_iou_threshold)
self.find_entry.bind('<Return>', self.findname)
self.find_entry.bind('<KP_Enter>', self.findname)
self.combo_category.bind('<<ComboboxSelected>>', self.combobox_change)
self.window.mainloop()
