9797 " dataset_root_name = os.path.basename(os.path.normpath(dataset_path))\n " ,
9898 " project_dir = os.path.join(default_paths.WORK_DIR, dataset_root_name)\n " ,
9999 " \n " ,
100+ " # Set if the worm is lighter than the background in the image\n " ,
101+ " # in the sample data, the worm is darker so we set this variable to False\n " ,
102+ " worm_is_lighter = False\n " ,
103+ " \n " ,
100104 " # This function loads the dataset\n " ,
101105 " # optional fields: there is an optional resize parameter to resize the images\n " ,
102106 " # also you can select specific videos from the dataset instead of loading them all\n " ,
103- " dataset = load_dataset(dataset_loader, dataset_path)"
107+ " dataset = load_dataset(dataset_loader, dataset_path, worm_is_lighter=worm_is_lighter )"
104108 ]
105109 },
106110 {
153157 " from wormpose.demo.synthetic_simple_visualizer import SyntheticSimpleVisualizer\n " ,
154158 " from ipython_utils import ImagesViewer, display_as_slider\n " ,
155159 " \n " ,
156- " synth_viz = SyntheticSimpleVisualizer(dataset_loader, dataset_path).generate()\n " ,
160+ " synth_viz = SyntheticSimpleVisualizer(dataset_loader,\n " ,
161+ " dataset_path, \n " ,
162+ " worm_is_lighter=worm_is_lighter).generate()\n " ,
157163 " img_viewer, img_viewer_plot = ImagesViewer(), ImagesViewer()\n " ,
158164 " num_images = 50\n " ,
159165 " \n " ,
194200 " from wormpose.demo.real_simple_visualizer import RealSimpleVisualizer\n " ,
195201 " from ipython_utils import ImagesViewer, display_as_slider\n " ,
196202 " \n " ,
197- " viz = RealSimpleVisualizer(dataset_loader, dataset_path).generate()\n " ,
203+ " viz = RealSimpleVisualizer(dataset_loader, \n " ,
204+ " dataset_path, \n " ,
205+ " worm_is_lighter=worm_is_lighter).generate()\n " ,
198206 " orig_img_viewer, processed_img_viewer = ImagesViewer(), ImagesViewer()\n " ,
199207 " \n " ,
200208 " max_viz = 100\n " ,
234242 " from wormpose.commands import calibrate\n " ,
235243 " from ipython_utils import ImagesViewer\n " ,
236244 " \n " ,
237- " video_name, result_file = next(calibrate(dataset_loader, dataset_path, save_images=True))\n " ,
245+ " video_name, result_file = next(calibrate(dataset_loader, \n " ,
246+ " dataset_path, \n " ,
247+ " worm_is_lighter=worm_is_lighter,\n " ,
248+ " save_images=True))\n " ,
238249 " \n " ,
239250 " VIEW_SCORES = 5\n " ,
240251 " \n " ,
285296 " display(fp)\n " ,
286297 " \n " ,
287298 " gen_progress = generate(dataset_loader,\n " ,
288- " dataset_path, \n " ,
299+ " dataset_path,\n " ,
300+ " worm_is_lighter=worm_is_lighter,\n " ,
289301 " num_train_samples=1000)\n " ,
290302 " for progress_value in gen_progress:\n " ,
291303 " fp.value = progress_value"
447459 "name" : " python" ,
448460 "nbconvert_exporter" : " python" ,
449461 "pygments_lexer" : " ipython3" ,
450- "version" : " 3.6.5 "
462+ "version" : " 3.8.6 "
451463 }
452464 },
453465 "nbformat" : 4 ,
454466 "nbformat_minor" : 4
455- }
467+ }
0 commit comments