import base64 import io import os.path as osp import warnings import numpy as np import PIL.Image import PIL.ImageDraw from labelme import logger def label_colormap(N=256): def bitget(byteval, idx): return ((byteval & (1 << idx)) != 0) cmap = np.zeros((N, 3)) for i in range(0, N): id = i r, g, b = 0, 0, 0 for j in range(0, 8): r = np.bitwise_or(r, (bitget(id, 0) << 7 - j)) g = np.bitwise_or(g, (bitget(id, 1) << 7 - j)) b = np.bitwise_or(b, (bitget(id, 2) << 7 - j)) id = (id >> 3) cmap[i, 0] = r cmap[i, 1] = g cmap[i, 2] = b cmap = cmap.astype(np.float32) / 255 return cmap def labelcolormap(N=256): warnings.warn('labelcolormap is deprecated. Please use label_colormap.') return label_colormap(N=N) # similar function as skimage.color.label2rgb def label2rgb(lbl, img=None, n_labels=None, alpha=0.3, thresh_suppress=0): if n_labels is None: n_labels = len(np.unique(lbl)) cmap = label_colormap(n_labels) cmap = (cmap * 255).astype(np.uint8) lbl_viz = cmap[lbl] lbl_viz[lbl == -1] = (0, 0, 0) # unlabeled if img is not None: img_gray = PIL.Image.fromarray(img).convert('LA') img_gray = np.asarray(img_gray.convert('RGB')) # img_gray = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY) # img_gray = cv2.cvtColor(img_gray, cv2.COLOR_GRAY2RGB) lbl_viz = alpha * lbl_viz + (1 - alpha) * img_gray lbl_viz = lbl_viz.astype(np.uint8) return lbl_viz def img_b64_to_array(img_b64): warnings.warn('img_ba64_to_array is deprecated. ' 'Please use img_b64_to_arr.') return img_b64_to_arr(img_b64) def img_b64_to_arr(img_b64): f = io.BytesIO() f.write(base64.b64decode(img_b64)) img_arr = np.array(PIL.Image.open(f)) return img_arr def img_arr_to_b64(img_arr): img_pil = PIL.Image.fromarray(img_arr) f = io.BytesIO() img_pil.save(f, format='PNG') img_bin = f.getvalue() img_b64 = base64.encodestring(img_bin) return img_b64 def polygons_to_mask(img_shape, polygons): mask = np.zeros(img_shape[:2], dtype=np.uint8) mask = PIL.Image.fromarray(mask) xy = list(map(tuple, polygons)) PIL.ImageDraw.Draw(mask).polygon(xy=xy, outline=1, fill=1) mask = np.array(mask, dtype=bool) return mask def draw_label(label, img=None, label_names=None, colormap=None): import matplotlib.pyplot as plt backend_org = plt.rcParams['backend'] plt.switch_backend('agg') plt.subplots_adjust(left=0, right=1, top=1, bottom=0, wspace=0, hspace=0) plt.margins(0, 0) plt.gca().xaxis.set_major_locator(plt.NullLocator()) plt.gca().yaxis.set_major_locator(plt.NullLocator()) if label_names is None: label_names = [str(l) for l in range(label.max() + 1)] if colormap is None: colormap = label_colormap(len(label_names)) label_viz = label2rgb(label, img, n_labels=len(label_names)) plt.imshow(label_viz) plt.axis('off') plt_handlers = [] plt_titles = [] for label_value, label_name in enumerate(label_names): if label_value not in label: continue if label_name.startswith('_'): continue fc = colormap[label_value] p = plt.Rectangle((0, 0), 1, 1, fc=fc) plt_handlers.append(p) plt_titles.append('{value}: {name}' .format(value=label_value, name=label_name)) plt.legend(plt_handlers, plt_titles, loc='lower right', framealpha=.5) f = io.BytesIO() plt.savefig(f, bbox_inches='tight', pad_inches=0) plt.cla() plt.close() plt.switch_backend(backend_org) out_size = (label_viz.shape[1], label_viz.shape[0]) out = PIL.Image.open(f).resize(out_size, PIL.Image.BILINEAR).convert('RGB') out = np.asarray(out) return out def shapes_to_label(img_shape, shapes, label_name_to_value, type='class'): assert type in ['class', 'instance'] cls = np.zeros(img_shape[:2], dtype=np.int32) if type == 'instance': ins = np.zeros(img_shape[:2], dtype=np.int32) instance_names = ['_background_'] for shape in shapes: polygons = shape['points'] label = shape['label'] if type == 'class': cls_name = label elif type == 'instance': cls_name = label.split('-')[0] if label not in instance_names: instance_names.append(label) ins_id = len(instance_names) - 1 cls_id = label_name_to_value[cls_name] mask = polygons_to_mask(img_shape[:2], polygons) cls[mask] = cls_id if type == 'instance': ins[mask] = ins_id if type == 'instance': return cls, ins return cls def labelme_shapes_to_label(img_shape, shapes): warnings.warn('labelme_shapes_to_label is deprecated, so please use ' 'shapes_to_label.') label_name_to_value = {'_background_': 0} for shape in shapes: label_name = shape['label'] if label_name in label_name_to_value: label_value = label_name_to_value[label_name] else: label_value = len(label_name_to_value) label_name_to_value[label_name] = label_value lbl = shapes_to_label(img_shape, shapes, label_name_to_value) return lbl, label_name_to_value def lblsave(filename, lbl): if osp.splitext(filename)[1] != '.png': filename += '.png' # Assume label ranses [-1, 254] for int32, # and [0, 255] for uint8 as VOC. if lbl.min() >= -1 and lbl.max() < 255: lbl_pil = PIL.Image.fromarray(lbl.astype(np.uint8), mode='P') colormap = label_colormap(255) lbl_pil.putpalette((colormap * 255).astype(np.uint8).flatten()) lbl_pil.save(filename) else: logger.warn( '[%s] Cannot save the pixel-wise class label as PNG, ' 'so please use the npy file.' % filename )