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Fix Default Dataset Not Loading on Startup and Improve Prediction Display After Annotation Selection #4

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Fix Default Dataset Not Loading on Startup and Improve Prediction Display After Annotation Selection #4

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18 changes: 11 additions & 7 deletions tools/vis_tools/windows/main_window.py
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Original file line number Diff line number Diff line change
@@ -1,14 +1,14 @@
import os
import pickle
import numpy as np
from loguru import logger
from utils import common
from utils import gl_engine as gl
from pcdet.datasets import PI3DET_Dataset
from PyQt5.QtCore import Qt, pyqtSignal
from PyQt5.QtWidgets import QWidget
from PyQt5.QtWidgets import QApplication, QWidget, QVBoxLayout, QHBoxLayout, QComboBox, QPushButton, QFileDialog,\
QLabel, QLineEdit, QListWidget
import numpy as np
from pcdet.datasets import PI3DET_Dataset
from loguru import logger
from utils import common
from utils import gl_engine as gl

class CustomListWidget(QListWidget):

Expand Down Expand Up @@ -58,6 +58,8 @@ def init_dataload_window(self):
self.split_select_cbox.addItems([
'training', 'validation'
])
# default selection
self.dataset_split = 'training'

# load dataset button
self.load_dataset_button = QPushButton('Load Dataset')
Expand Down Expand Up @@ -127,7 +129,7 @@ def load_dataset(self):
self.dataset = PI3DET_Dataset(
dataset_cfg=dataset_cfg,
class_names=['Car', 'Pedestrian'],
training=self.dataset_split == 'training',
training= (self.dataset_split == 'training'),
root_path=dataset_cfg.DATA_PATH
)
self.frames_count = len(self.dataset)
Expand Down Expand Up @@ -203,7 +205,7 @@ def show_boxes(self):

if hasattr(self, 'predict_infos'):
boxes_3d = self.predict_infos[self.sample_index]['boxes_lidar']
labels = self.predict_infos[self.sample_index]['pred_labels'][:, None] + 2
labels = self.predict_infos[self.sample_index]['pred_labels'][:, None] + 10
boxes_3d = np.hstack([boxes_3d, labels])
box_info = gl.create_boxes(bboxes_3d=boxes_3d)
for box_item, l1_item, l2_item in zip(box_info['box_items'], box_info['l1_items'],\
Expand All @@ -228,6 +230,8 @@ def load_pred_pkl(self):
f = open(file, 'rb')
anno_list = pickle.load(f)
self.predict_infos = anno_list
# show prediction after select annotation
self.show_sample()

def show_sample(self):
self.reset_viewer()
Expand Down