/
annotator_video.py
1664 lines (1467 loc) · 62.1 KB
/
annotator_video.py
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import sys
import functools
import cv2
import glob
import os
import os.path as osp
import imgviz
import html
import json
import math
import argparse
import numpy as np
import tempfile
import torch
import torch.nn.functional as F
import base64
from PyQt5.QtWidgets import QWidget, QApplication, QMainWindow, QApplication, QPushButton, QLabel, QFileDialog, QProgressBar, QComboBox, QScrollArea, QDockWidget, QMessageBox
from PyQt5.QtGui import QPixmap, QIcon, QImage
from PyQt5.Qt import QSize
from qtpy.QtCore import Qt
from qtpy import QtCore
from qtpy import QtGui, QtWidgets
from canvas import Canvas
import utils
from utils.download_model import download_model
from labelme.widgets import ToolBar, UniqueLabelQListWidget, LabelDialog, LabelListWidget, LabelListWidgetItem, ZoomWidget
from labelme import PY2
from labelme.label_file import LabelFile
from labelme.label_file import LabelFileError
from shape import Shape
from PIL import Image
from collections import namedtuple
Click = namedtuple('Click', ['is_positive', 'coords'])
from segment_anything import sam_model_registry, SamPredictor
sys.path.insert(0, 'STCN/')
from model.eval_network import STCN
import torch
from torchvision import transforms
from dataset.range_transform import im_normalization
from app_inference_core import InferenceCore
from util.tensor_util import unpad, pad_divide_by
LABEL_COLORMAP = imgviz.label_colormap()
class MainWindow(QMainWindow):
FIT_WINDOW, FIT_WIDTH, MANUAL_ZOOM = 0, 1, 2
def __init__(self, parent=None, global_w=1000, global_h=1800, model_type='vit_b', keep_input_size=True, max_size=720,max_size_STCN=600):
super(MainWindow, self).__init__(parent)
self.resize(global_w, global_h)
self.model_type = model_type
self.keep_input_size = keep_input_size
self.max_size = float(max_size)
self.max_size_STCN = float(max_size_STCN)
self.setWindowTitle('segment-anything-annotator')
self.canvas = Canvas(self,
epsilon=10.0,
double_click='close',
num_backups=10,
app=self,
)
self._noSelectionSlot = False
self.current_output_dir = 'output'
os.makedirs(self.current_output_dir, exist_ok=True)
self.current_output_filename = ''
self.canvas.zoomRequest.connect(self.zoomRequest)
self.memory_shapes = []
self.sam_mask = []
self.sam_mask_proposal = []
self.image_encoded_flag = False
self.min_point_dis = 4
self.predictor = None
self.prop_model = None
self.processor = None
self.tracked_id_list = None
self.tracked_label_list = None
self.scroll_values = {
Qt.Horizontal: {},
Qt.Vertical: {},
}
self.scrollArea = QScrollArea(self)
self.scrollArea.setWidget(self.canvas)
self.scrollArea.setWidgetResizable(True)
self.scrollBars = {
Qt.Vertical: self.scrollArea.verticalScrollBar(),
Qt.Horizontal: self.scrollArea.horizontalScrollBar(),
}
self.canvas.scrollRequest.connect(self.scrollRequest)
self.canvas.newShape.connect(self.newShape)
self.canvas.shapeMoved.connect(self.setDirty)
self.canvas.selectionChanged.connect(self.shapeSelectionChanged)
self.canvas.drawingPolygon.connect(self.toggleDrawingSensitive)
self.uniqLabelList = UniqueLabelQListWidget()
self.uniqLabelList.setToolTip(
self.tr(
"Select label to start annotating for it. "
"Press 'Esc' to deselect."
)
)
self.labelDialog = LabelDialog(
parent=self,
labels=[],
sort_labels=False,
show_text_field=True,
completion='contains',
fit_to_content={'column': True, 'row': False},
)
self.labelList = LabelListWidget()
self.labelList.itemSelectionChanged.connect(self.labelSelectionChanged)
self.labelList.itemDoubleClicked.connect(self.editLabel)
self.labelList.itemChanged.connect(self.labelItemChanged)
self.labelList.itemDropped.connect(self.labelOrderChanged)
self.shape_dock = QDockWidget(
self.tr("Polygon Labels"), self
)
self.shape_dock.setObjectName("Labels")
self.shape_dock.setWidget(self.labelList)
self.category_list = [i.strip() for i in open('categories.txt', 'r', encoding='utf-8').readlines()]
self.labelDialog = LabelDialog(
parent=self,
labels=self.category_list,
sort_labels=False,
show_text_field=True,
completion='contains',
fit_to_content={'column': True, 'row': False},
)
self.zoom_values = {}
self.video_directory = ''
self.video_list = []
self.video_len = len(self.video_list)
self.img_list = []
self.img_len = len(self.img_list)
self.current_img_index = 0
self.current_img = ''
self.current_img_data = ''
self.video_list = []
self.video_len = len(self.video_list)
self.current_video_index = 0
self.current_video = ''
self.button_next = QPushButton('Next Image (n)', self)
self.button_next.clicked.connect(self.clickButtonNext)
self.button_next.setShortcut('n')
self.button_last = QPushButton('Last Image (b)', self)
self.button_last.clicked.connect(self.clickButtonLast)
self.button_last.setShortcut('b')
self.button_next_video = QPushButton('Next Video', self)
self.button_next_video.clicked.connect(self.clickButtonNextVideo)
self.button_last_video = QPushButton('Last Video', self)
self.button_last_video.clicked.connect(self.clickButtonLastVideo)
self.img_progress_bar = QProgressBar(self)
self.img_progress_bar.setMinimum(0)
self.img_progress_bar.setMaximum(1)
self.img_progress_bar.setValue(0)
self.video_progress_bar = QProgressBar(self)
self.video_progress_bar.setMinimum(0)
self.video_progress_bar.setMaximum(1)
self.video_progress_bar.setValue(0)
self.button_proposal1 = QPushButton('Proposal1', self)
self.button_proposal1.clicked.connect(self.choose_proposal1)
self.button_proposal1.setShortcut('1')
self.button_proposal2 = QPushButton('Proposal2', self)
self.button_proposal2.clicked.connect(self.choose_proposal2)
self.button_proposal2.setShortcut('2')
self.button_proposal3 = QPushButton('Proposal3', self)
self.button_proposal3.clicked.connect(self.choose_proposal3)
self.button_proposal3.setShortcut('3')
self.button_proposal_list = [self.button_proposal1, self.button_proposal2, self.button_proposal3]
self.button_add_track = QPushButton('Add objects to memory', self)
self.button_add_track.clicked.connect(self.clickAddMemory)
self.button_add_key_frame = QPushButton('Add as key frame', self)
self.button_add_key_frame.clicked.connect(self.clickAddKeyFrame)
self.button_propagate = QPushButton('Propagate (SPACE)', self)
self.button_propagate.setShortcut(' ')
self.button_propagate.clicked.connect(self.clickPropagate)
self.button_clear_track_memory = QPushButton('Clear track memory', self)
self.button_clear_track_memory.clicked.connect(self.clickClearTrackMemory)
self.class_on_flag = True
self.class_on_text = QLabel("Class On", self)
self.tracked_object_text = QLabel("Tracked_object:", self)
#naive layout
self.scrollArea.move(int(0.02 * global_w), int(0.08 * global_h))
self.scrollArea.resize(int(0.75 * global_w), int(0.7 * global_h))
self.shape_dock.move(int(0.79 * global_w), int(0.08 * global_h))
self.shape_dock.resize(int(0.2 * global_w), int(0.7 * global_h))
self.button_next.move(int(0.14 * global_w), int(0.82 * global_h))
self.button_next.resize(int(0.13 * global_w),int(0.04 * global_h))
self.button_last.move(int(0.01 * global_w), int(0.82 * global_h))
self.button_last.resize(int(0.13 * global_w),int(0.04 * global_h))
self.button_next_video.resize(int(0.13 * global_w),int(0.04 * global_h))
self.button_next_video.move(int(0.14 * global_w), int(0.89 * global_h))
self.button_last_video.resize(int(0.13 * global_w),int(0.04 * global_h))
self.button_last_video.move(int(0.01 * global_w), int(0.89 * global_h))
self.img_progress_bar.move(int(0.01 * global_w), int(0.8 * global_h))
self.img_progress_bar.resize(int(0.25 * global_w),int(0.02 * global_h))
self.video_progress_bar.move(int(0.01 * global_w), int(0.87 * global_h))
self.video_progress_bar.resize(int(0.25 * global_w),int(0.02 * global_h))
self.button_proposal1.resize(int(0.17 * global_w),int(0.14 * global_h))
self.button_proposal1.move(int(0.27 * global_w), int(0.8 * global_h))
self.button_proposal2.resize(int(0.17 * global_w),int(0.14 * global_h))
self.button_proposal2.move(int(0.44 * global_w), int(0.8 * global_h))
self.button_proposal3.resize(int(0.17 * global_w),int(0.14 * global_h))
self.button_proposal3.move(int(0.61 * global_w), int(0.8 * global_h))
self.class_on_text.move(int(0.8 * global_w), int(0.78 * global_h))
self.tracked_object_text.resize(int(0.2 * global_w), int(0.04 * global_h))
self.tracked_object_text.move(int(0.8 * global_w), int(0.81 * global_h))
self.button_add_track.resize(int(0.2 * global_w), int(0.04 * global_h))
self.button_add_track.move(int(0.8 * global_w), int(0.85 * global_h))
self.button_add_key_frame.resize(int(0.2 * global_w), int(0.04 * global_h))
self.button_add_key_frame.move(int(0.8 * global_w), int(0.89 * global_h))
self.button_propagate.resize(int(0.2 * global_w), int(0.04 * global_h))
self.button_propagate.move(int(0.8 * global_w), int(0.93 * global_h))
self.button_clear_track_memory.resize(int(0.2 * global_w), int(0.03 * global_h))
self.button_clear_track_memory.move(int(0.8 * global_w), int(0.97 * global_h))
self.zoomWidget = ZoomWidget()
action = functools.partial(utils.newAction, self)
categoryFile = action(
self.tr("Category File"),
lambda: self.clickCategoryChoose(),
'None',
"objects",
self.tr("Category File"),
enabled=True,
)
imageDirectory = action(
self.tr("Video Directory"),
lambda: self.clickFileChoose(),
'None',
"objects",
self.tr("Video Directory"),
enabled=True,
)
LoadSAM = action(
self.tr("Load SAM"),
lambda: self.clickLoadSAM(),
'None',
"objects",
self.tr("Load SAM"),
enabled=True,
)
LoadSTCN = action(
self.tr("Load STCN"),
lambda: self.clickLoadSTCN(),
'None',
"objects",
self.tr("Load STCN"),
enabled=True,
)
AutoSeg = action(
self.tr("AutoSeg"),
lambda: self.clickAutoSeg(),
'None',
"objects",
self.tr("AutoSeg"),
enabled=False,
)
promptSeg = action(
self.tr("(A)ccept"),
lambda: self.addSamMask(),
'a',
"objects",
self.tr("(A)ccept"),
enabled=False,
)
saveDirectory = action(
self.tr("Save Directory"),
lambda: self.clickSaveChoose(),
'None',
"objects",
self.tr("Save Directory"),
enabled=True,
)
createMode = action(
self.tr("Manual Polygons"),
lambda: self.toggleDrawMode(False, createMode="polygon"),
'Ctrl+W',
"objects",
self.tr("Start drawing polygons"),
enabled=True,
)
createPointMode = action(
self.tr("Point Prompt"),
lambda: self.toggleDrawMode(False, createMode="point"),
'None',
"objects",
self.tr("Point Prompt"),
enabled=True,
)
createRectangleMode = action(
self.tr("Box Prompt"),
lambda: self.toggleDrawMode(False, createMode="rectangle"),
'None',
"objects",
self.tr("Box Prompt"),
enabled=True,
)
cleanPrompt = action(
self.tr("(R)eject"),
lambda: self.cleanPrompt(),
'r',
"objects",
self.tr("(R)eject"),
enabled=True,
)
self.switchClass = action(
self.tr("Class On/Off"),
lambda: self.clickSwitchClass(),
'none',
"objects",
self.tr("Class On/Off"),
enabled=True,
)
editMode = action(
self.tr("(E)dit Polygons"),
self.setEditMode,
'e',
"edit",
self.tr("Move and edit the selected polygons"),
enabled=False,
)
saveAs = action(
self.tr("&Save As"),
self.saveFileAs,
'ALT+s',
"save-as",
self.tr("Save labels to a different file"),
enabled=True,
)
hideAll = action(
self.tr("&Hide\nPolygons"),
functools.partial(self.togglePolygons, False),
icon="eye",
tip=self.tr("Hide all polygons"),
enabled=False,
)
showAll = action(
self.tr("&Show\nPolygons"),
functools.partial(self.togglePolygons, True),
icon="eye",
tip=self.tr("Show all polygons"),
enabled=False,
)
save = action(
self.tr("&(S)ave"),
self.saveFile,
'S',
"save",
self.tr("Save labels to file"),
enabled=False,
)
delete = action(
self.tr("(D)elete Polygons"),
self.deleteSelectedShape,
'd',
"cancel",
self.tr("Delete the selected polygons"),
enabled=False,
)
reduce_point = action(
self.tr("Reduce Points"),
self.reducePoint,
'None',
"copy",
self.tr("Reduce Points"),
enabled=True,
)
self.actions = utils.struct(
categoryFile=categoryFile,
imageDirectory=imageDirectory,
saveDirectory=saveDirectory,
switchClass=self.switchClass,
loadSTCN=LoadSTCN,
loadSAM=LoadSAM,
#autoSeg=AutoSeg,
promptSeg=promptSeg,
cleanPrompt=cleanPrompt,
createMode=createMode,
createPointMode=createPointMode,
createRectangleMode=createRectangleMode,
editMode=editMode,
delete=delete,
reduce_point=reduce_point,
save=save,
onShapesPresent=(saveAs, hideAll, showAll),
menu=(
createMode,
editMode,
save,
)
)
# Custom context menu for the canvas widget:
utils.addActions(self.canvas.menus[0], self.actions.menu)
utils.addActions(
self.canvas.menus[1],
(
action("&Copy here", self.copyShape),
action("&Move here", self.moveShape),
),
)
self.toolbar = self.addToolBar('Tool')
self.toolbar.addAction(categoryFile)
self.toolbar.addAction(imageDirectory)
self.toolbar.addAction(saveDirectory)
self.toolbar.addAction(self.switchClass)
self.toolbar.addAction(LoadSTCN)
self.toolbar.addAction(LoadSAM)
#self.toolbar.addAction(AutoSeg)
self.toolbar.addAction(promptSeg)
self.toolbar.addAction(cleanPrompt)
self.toolbar.addAction(createMode)
self.toolbar.addAction(createPointMode)
self.toolbar.addAction(createRectangleMode)
self.toolbar.addAction(editMode)
self.toolbar.addAction(delete)
self.toolbar.addAction(reduce_point)
self.toolbar.addAction(save)
self.toolbar.setToolButtonStyle(Qt.ToolButtonTextOnly)
zoom = QtWidgets.QWidgetAction(self)
zoom.setDefaultWidget(self.zoomWidget)
self.zoomWidget.setWhatsThis(
str(
self.tr(
"Zoom in or out of the image. Also accessible with "
"{} from the canvas."
)
).format(
#utils.fmtShortcut(
# "{},{}".format(shortcuts["zoom_in"], shortcuts["zoom_out"])
#),
utils.fmtShortcut(self.tr("Ctrl+Wheel")),
)
)
self.zoomWidget.setEnabled(True)
self.zoomWidget.valueChanged.connect(self.paintCanvas)
self.canvas.actions = self.actions
def saveFileAs(self, _value=False):
assert not self.image.isNull(), "cannot save empty image"
self._saveFile(self.saveFileDialog())
def saveFile(self, _value=False):
# assert not self.image.isNull(), "cannot save empty image"
# if self.labelFile:
# # DL20180323 - overwrite when in directory
# self._saveFile(self.labelFile.filename)
# elif self.output_file:
# self._saveFile(self.output_file)
# self.close()
# else:
# self._saveFile(self.saveFileDialog())
#self._saveFile(self.saveFileDialog())
#print(self.current_output_filename)
self._saveFile(self.current_output_filename)
def _saveFile(self, filename):
video_name = os.path.basename(os.path.basename(self.current_video))
os.makedirs(os.path.join(self.current_output_dir, video_name), exist_ok=True)
if filename and self.saveLabels(filename):
self.setClean()
def saveLabels(self, filename):
lf = LabelFile()
def format_shape(s):
data = s.other_data.copy()
data.update(
dict(
label=s.label.encode("utf-8") if PY2 else s.label,
points=[[p.x(), p.y()] for p in s.points],
group_id=s.group_id,
description="",
shape_type=s.shape_type,
flags=s.flags,
)
)
return data
shapes = [format_shape(item.shape()) for item in self.labelList]
imageData = base64.b64encode(self.current_img_data).decode("utf-8")
save_data = {
"version": "1.0.0",
"flags": {},
"shapes": shapes,
"imagePath": self.current_img,
"imageData": imageData,
"imageHeight": self.raw_h,
"imageWidth": self.raw_w
}
with open(filename, 'w') as f:
json.dump(save_data, f)
return True
def setClean(self):
self.dirty = False
self.actions.save.setEnabled(False)
self.actions.createMode.setEnabled(True)
def saveFileDialog(self):
caption = self.tr("Choose File")
filters = self.tr("Label files")
if self.output_dir:
dlg = QtWidgets.QFileDialog(
self, caption, self.output_dir, filters
)
else:
dlg = QtWidgets.QFileDialog(
self, caption, self.currentPath(), filters
)
dlg.setDefaultSuffix(LabelFile.suffix[1:])
dlg.setAcceptMode(QtWidgets.QFileDialog.AcceptSave)
dlg.setOption(QtWidgets.QFileDialog.DontConfirmOverwrite, False)
dlg.setOption(QtWidgets.QFileDialog.DontUseNativeDialog, False)
basename = os.path.basename(self.current_img)[:-4]
if self.output_dir:
default_labelfile_name = osp.join(
self.output_dir, basename + LabelFile.suffix
)
else:
default_labelfile_name = osp.join(
self.currentPath(), basename + LabelFile.suffix
)
filename = dlg.getSaveFileName(
self,
self.tr("Choose File"),
default_labelfile_name,
self.tr("Label files (*%s)") % LabelFile.suffix,
)
if isinstance(filename, tuple):
filename, _ = filename
return filename
def currentPath(self):
#return osp.dirname(str(self.filename)) if self.filename else "."
return "."
def loadAnno(self, filename):
with open(filename,'r') as f:
data = json.load(f)
for shape in data['shapes']:
label = shape["label"]
try:
ttt = int(label)
label = self.category_list[ttt]
except:
pass
points = shape["points"]
shape_type = shape["shape_type"]
flags = shape["flags"]
group_id = shape["group_id"]
if not points:
# skip point-empty shape
continue
shape = Shape(
label=label,
shape_type=shape_type,
group_id=group_id,
flags=flags
)
for x, y in points:
shape.addPoint(QtCore.QPointF(x, y))
shape.close()
self.addLabel(shape)
self.canvas.loadShapes([item.shape() for item in self.labelList])
def clickButtonNext(self):
if self.actions.save.isEnabled():
self.saveFile()
if self.current_img_index < self.img_len - 1:
self.current_img_index += 1
self.current_img = self.img_list[self.current_img_index]
self.loadImg()
def clickButtonLast(self):
if self.actions.save.isEnabled():
self.saveFile()
if self.current_img_index > 0:
self.current_img_index -= 1
self.current_img = self.img_list[self.current_img_index]
self.loadImg()
def clickButtonNextVideo(self):
if self.actions.save.isEnabled():
self.saveFile()
if self.current_video_index < self.video_len - 1:
self.current_video_index += 1
self.current_video = self.video_list[self.current_video_index]
self.video_progress_bar.setValue(self.current_video_index)
self.img_list = glob.glob(os.path.join(self.current_video, '*.jpg')) + glob.glob(os.path.join(self.current_video, '*.png'))
self.img_list.sort()
self.img_len = len(self.img_list)
self.current_img_index = 0
self.current_img = self.img_list[self.current_img_index]
self.loadImg()
self.clickClearTrackMemory()
def clickButtonLastVideo(self):
if self.actions.save.isEnabled():
self.saveFile()
if self.current_video_index > 0:
self.current_video_index -= 1
self.current_video = self.video_list[self.current_video_index]
self.video_progress_bar.setValue(self.current_video_index)
self.img_list = glob.glob(os.path.join(self.current_video, '*.jpg')) + glob.glob(os.path.join(self.current_video, '*.png'))
self.img_list.sort()
self.img_len = len(self.img_list)
self.current_img_index = 0
self.current_img = self.img_list[self.current_img_index]
self.loadImg()
self.clickClearTrackMemory()
def choose_proposal1(self):
if len(self.sam_mask_proposal) > 0:
self.sam_mask = self.sam_mask_proposal[0]
self.canvas.setHiding()
self.canvas.update()
def choose_proposal2(self):
if len(self.sam_mask_proposal) > 1:
self.sam_mask = self.sam_mask_proposal[1]
self.canvas.setHiding()
self.canvas.update()
def choose_proposal3(self):
if len(self.sam_mask_proposal) > 2:
self.sam_mask = self.sam_mask_proposal[2]
self.canvas.setHiding()
self.canvas.update()
def choose_proposal4(self):
if len(self.sam_mask_proposal) > 3:
self.sam_mask = self.sam_mask_proposal[3]
self.canvas.setHiding()
self.canvas.update()
def loadImg(self):
self.raw_h, self.raw_w = cv2.imread(self.current_img).shape[:2]
pixmap = QPixmap(self.current_img)
#pixmap = pixmap.scaled(int(0.75 * global_w), int(0.7 * global_h))
self.canvas.loadPixmap(pixmap)
img_name = os.path.basename(self.current_img)[:-4]
video_name = os.path.basename(self.current_video)
self.current_output_filename = os.path.join(self.current_output_dir, video_name, img_name + '.json')
self.labelList.clear()
if os.path.isfile(self.current_output_filename):
self.loadAnno(self.current_output_filename)
self.image_encoded_flag = False
self.img_progress_bar.setMinimum(0)
self.img_progress_bar.setMaximum(self.img_len-1)
self.img_progress_bar.setValue(self.current_img_index)
self.current_img_data = LabelFile.load_image_file(self.current_img)
def clickFileChoose(self):
directory = QFileDialog.getExistingDirectory(self, 'choose target fold','.')
if directory == '':
return
#self.img_list = glob.glob(directory + '/*.{jpg,png,JPG,PNG}')
self.video_list = glob.glob(directory + '/*')
self.video_list.sort()
self.video_len = len(self.video_list)
if self.video_len == 0:
return
self.video_progress_bar.setMinimum(0)
self.video_progress_bar.setMaximum(self.video_len-1)
self.current_video_index = 0
self.current_video = self.video_list[self.current_video_index]
self.img_list = glob.glob(self.video_list[0] + '/*.jpg') + glob.glob(self.video_list[0] + '/*.png')
self.img_list.sort()
self.img_len = len(self.img_list)
if self.img_len == 0:
return
self.current_img_index = 0
self.current_img = self.img_list[self.current_img_index]
self.loadImg()
def clickSaveChoose(self):
directory = QFileDialog.getExistingDirectory(self, 'choose target fold','.')
if directory == '':
return
else:
self.current_output_dir = directory
os.makedirs(self.current_output_dir, exist_ok=True)
self.loadImg()
return directory
def clickSwitchClass(self):
if self.class_on_flag:
self.class_on_flag = False
self.class_on_text.setText('Class Off')
else:
self.class_on_flag = True
self.class_on_text.setText('Class On')
def clickCategoryChoose(self):
filename, _ = QFileDialog.getOpenFileName(self, 'choose target file','.')
try:
with open(filename, 'r') as f:
data = f.readlines()
self.category_list = [i.strip() for i in data]
self.category_list.sort()
self.labelDialog = LabelDialog(
parent=self,
labels=self.category_list,
sort_labels=False,
show_text_field=True,
completion='contains',
fit_to_content={'column': True, 'row': False},
)
except Exception as e:
pass
def clickLoadSAM(self):
download_model(self.model_type)
self.sam = sam_model_registry[self.model_type](checkpoint='{}.pth'.format(self.model_type))
self.device = "cuda" if torch.cuda.is_available() else "cpu"
self.sam.to(device=self.device)
self.predictor = SamPredictor(self.sam)
self.actions.loadSAM.setEnabled(False)
#self.actions.autoSeg.setEnabled(True)
self.actions.promptSeg.setEnabled(True)
def clickLoadSTCN(self):
self.device = "cuda" if torch.cuda.is_available() else "cpu"
self.prop_model = STCN().to(device=self.device).eval()
# Performs input mapping such that stage 0 model can be loaded
prop_saved = torch.load('stcn.pth',map_location=torch.device(self.device))
for k in list(prop_saved.keys()):
if k == 'value_encoder.conv1.weight':
if prop_saved[k].shape[1] == 4:
pads = torch.zeros((64,1,7,7), device=self.device)
prop_saved[k] = torch.cat([prop_saved[k], pads], 1)
self.prop_model.load_state_dict(prop_saved)
self.im_transform = transforms.Compose([
transforms.ToTensor(),
im_normalization,
])
self.actions.loadSTCN.setEnabled(False)
def clickAddMemory(self):
if self.prop_model == None:
return
def format_shape(s):
data = s.other_data.copy()
data.update(
dict(
label=s.label.encode("utf-8") if PY2 else s.label,
points=[(p.x(), p.y()) for p in s.points],
group_id=s.group_id,
shape_type=s.shape_type,
flags=s.flags,
)
)
return data
if len(self.img_list) != 0 and len(self.canvas.selectedShapes) > 0:
rgb = torch.stack([self.im_transform(Image.open(tmp_img).convert('RGB')) for tmp_img in self.img_list],0)
self.raw_h,self.raw_w = rgb.shape[-2:]
scale_ratio = self.max_size_STCN / max(self.raw_h, self.raw_w)
self.scaled_h, self.scaled_w = int(self.raw_h * scale_ratio), int(self.raw_w * scale_ratio)
rgb = F.interpolate(rgb, size=(self.scaled_h, self.scaled_w), mode='bilinear').unsqueeze(0)
self.memory_shapes = [format_shape(item) for item in self.canvas.selectedShapes]
used_mask_dic = {}
for shape in self.memory_shapes:
mask = torch.Tensor(self.polygon2mask(shape['points'],(self.raw_h,self.raw_w)))
if shape['group_id'] in used_mask_dic.keys():
used_mask_dic[shape['group_id']]['mask'] = used_mask_dic[shape['group_id']]['mask'] + mask
used_mask_dic[shape['group_id']]['mask'][used_mask_dic[shape['group_id']]['mask'] > 1] = 0
else:
used_mask_dic[shape['group_id']] = {}
used_mask_dic[shape['group_id']]['mask'] = mask
used_mask_dic[shape['group_id']]['label'] = shape['label']
self.processor = InferenceCore(self.prop_model, rgb.to(device=self.device), len(used_mask_dic.keys()), top_k=20,
mem_every=1000, include_last=True, device=self.device)
self.tracked_object_text.setText('Tracked_object:{}'.format(list(used_mask_dic.keys())))
mask = torch.stack([v['mask'] for _, v in used_mask_dic.items()],0).unsqueeze(1)
mask = F.interpolate(mask, size=(self.scaled_h, self.scaled_w), mode='nearest')
self.tracked_id_list = [k for k, _ in used_mask_dic.items()]
self.tracked_label_list = [v['label'] for _, v in used_mask_dic.items()]
self.addmemory(mask, self.current_img_index)
#self.canvas.selectedShapes = []
def addmemory(self, mask, frame_idx, is_temp=False):
with torch.no_grad():
mask, _ = pad_divide_by(mask, 16)
#self.prob[:, frame_idx] = aggregate(mask, keep_bg=True)
# KV pair for the interacting frame
key_k, _, qf16, _, _ = self.processor.encode_key(frame_idx)
key_v = self.processor.prop_net.encode_value(self.processor.images[:,frame_idx], qf16, mask.to(device=self.device))
key_k = key_k.unsqueeze(2)
self.processor.mem_bank.add_memory(key_k, key_v, is_temp)
def clickAddKeyFrame(self):
if self.processor == None or len(self.tracked_id_list) == 0:
return
def format_shape(s):
data = s.other_data.copy()
data.update(
dict(
label=s.label.encode("utf-8") if PY2 else s.label,
points=[(p.x(), p.y()) for p in s.points],
group_id=s.group_id,
shape_type=s.shape_type,
flags=s.flags,
)
)
return data
self.memory_shapes = [format_shape(item.shape()) for item in self.labelList]
used_mask_dic = {}
for shape in self.memory_shapes:
if shape['group_id'] not in self.tracked_id_list:
continue
mask = torch.Tensor(self.polygon2mask(shape['points'],(self.raw_h,self.raw_w)))
if shape['group_id'] in used_mask_dic.keys():
used_mask_dic[shape['group_id']]['mask'] = used_mask_dic[shape['group_id']]['mask'] + mask
used_mask_dic[shape['group_id']]['mask'][used_mask_dic[shape['group_id']]['mask'] > 1] = 0
else:
used_mask_dic[shape['group_id']] = {}
used_mask_dic[shape['group_id']]['mask'] = mask
used_mask_dic[shape['group_id']]['label'] = shape['label']
if len(used_mask_dic) != len(self.tracked_id_list):
return
mask = torch.stack([used_mask_dic[tid]['mask'] for tid in self.tracked_id_list],0).unsqueeze(1)
mask = F.interpolate(mask, size=(self.scaled_h, self.scaled_w), mode='nearest')
self.addmemory(mask, self.current_img_index)
self.processor.mem_bank.temp_k = None
self.processor.mem_bank.temp_v = None
def clickPropagate(self):
if self.processor == None or len(self.tracked_id_list) == 0:
return
with torch.no_grad():
k16, qv16, qf16, qf8, qf4 = self.processor.encode_key(self.current_img_index)
out_mask = self.processor.prop_net.segment_with_query(self.processor.mem_bank, qf8, qf4, k16, qv16)
prev_value = self.processor.prop_net.encode_value(self.processor.images[:,self.current_img_index], qf16, out_mask)
prev_key = k16.unsqueeze(2)
#self.processor.mem_bank.add_memory(prev_key, prev_value,is_temp=True)
self.processor.mem_bank.temp_k = prev_key.flatten(start_dim=2)
self.processor.mem_bank.temp_v = prev_value.flatten(start_dim=2)
prob = unpad(out_mask, self.processor.pad)
prob = (prob > 0.5).cpu().numpy()[:,0].astype(np.uint8)
out_masks = []
for i in range(prob.shape[0]):
out_masks.append(prob[i])
del prob, k16, qv16, qf16, qf8, qf4, prev_value, prev_key
torch.cuda.empty_cache()
updated_id_list = []
cur_shape = [item.shape() for item in self.labelList]
add_shape = []
vaild_contours_index = []
for i in range(len(out_masks)):
out_mask = out_masks[i]
if out_mask.sum() == 0:
continue
out_mask = cv2.resize(out_mask, (self.raw_w, self.raw_h), interpolation=cv2.INTER_NEAREST)
points_list = cv2.findContours(out_mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)[0]
area_list = []
for idx in range(len(points_list)):
area = cv2.contourArea(points_list[idx])
area_list.append(area)
max_idx = np.argmax(np.array(area_list))
#for points in points_list[max_idx:max_idx+1]:
for iii, points in enumerate(points_list):
if cv2.contourArea(points) < 100 and iii != max_idx:
continue
pointsx = points[:,0,0]
pointsy = points[:,0,1]
label = self.tracked_label_list[i]
shape_type = 'polygon'
group_id = int(self.tracked_id_list[i])
updated_id_list.append(group_id)
shape = Shape(
label=label,
shape_type=shape_type,
group_id=group_id,
)
for point_index in range(pointsx.shape[0]):
shape.addPoint(QtCore.QPointF(pointsx[point_index], pointsy[point_index]))
shape.close()
add_shape.append(shape)
add_shape_raw = [i for i in cur_shape if int(i.group_id) not in updated_id_list]
self.labelList.clear()
for shape in add_shape_raw + add_shape:
self.addLabel(shape)
self.canvas.loadShapes([item.shape() for item in self.labelList])
self.actions.save.setEnabled(True)
def clickClearTrackMemory(self):
del self.processor, self.tracked_id_list, self.tracked_label_list
self.processor = None
self.tracked_id_list = None
self.tracked_label_list = None
self.tracked_object_text.setText("Tracked_object:")
def clickAutoSeg(self):
pass
def getMaxId(self):
max_id = -1
for label in self.labelList:
if label.shape().group_id != None:
max_id = max(max_id, int(label.shape().group_id))
return max_id
def show_proposals(self, masks=None, flag=1):
if flag != 1:
img = cv2.imread(self.current_img)
if len(img.shape) == 2:
img = cv2.cvtColor(img, cv2.COLOR_GRAY2BGR)
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
for msk_idx in range(masks.shape[0]):
tmp_mask = masks[msk_idx]
tmp_vis = img.copy()
tmp_vis[tmp_mask > 0] = 0.5 * tmp_vis[tmp_mask > 0] + 0.5 * np.array([30,30,220])
tmp_vis = cv2.resize(tmp_vis,(int(0.17 * global_w),int(0.14 * global_h)))
tmp_vis = tmp_vis.astype(np.uint8)
pixmap = QPixmap.fromImage(QImage(tmp_vis, tmp_vis.shape[1], tmp_vis.shape[0], tmp_vis.shape[1] * 3 , QImage.Format_RGB888))
#self.button_proposal_list[msk_idx].setPixmap(pixmap)
self.button_proposal_list[msk_idx].setIcon(QIcon(pixmap))