diff --git a/detect.py b/detect.py index 88d1d9ca3800..db0c545b0635 100644 --- a/detect.py +++ b/detect.py @@ -156,7 +156,7 @@ def run(weights='yolov5s.pt', # model.pt path(s) if save_img or save_crop or view_img: # Add bbox to image c = int(cls) # integer class label = None if hide_labels else (names[c] if hide_conf else f'{names[c]} {conf:.2f}') - plot_one_box(xyxy, im0, label=label, color=colors(c, True), line_thickness=line_thickness) + im0 = plot_one_box(xyxy, im0, label=label, color=colors(c, True), line_width=line_thickness) if save_crop: save_one_box(xyxy, imc, file=save_dir / 'crops' / names[c] / f'{p.stem}.jpg', BGR=True) diff --git a/models/common.py b/models/common.py index 5ef3996007a2..35790804ca52 100644 --- a/models/common.py +++ b/models/common.py @@ -354,7 +354,7 @@ def display(self, pprint=False, show=False, save=False, crop=False, render=False if crop: save_one_box(box, im, file=save_dir / 'crops' / self.names[int(cls)] / self.files[i]) else: # all others - plot_one_box(box, im, label=label, color=colors(cls)) + im = plot_one_box(box, im, label=label, color=colors(cls)) else: str += '(no detections)' diff --git a/utils/general.py b/utils/general.py index c70c21f47636..4fc32f5691fc 100755 --- a/utils/general.py +++ b/utils/general.py @@ -110,9 +110,14 @@ def is_pip(): return 'site-packages' in Path(__file__).absolute().parts +def is_ascii(str=''): + # Is string composed of all ASCII (no UTF) characters? + return len(str.encode().decode('ascii', 'ignore')) == len(str) + + def emojis(str=''): # Return platform-dependent emoji-safe version of string - return str.encode().decode(encoding='ascii', errors='ignore') if platform.system() == 'Windows' else str + return str.encode().decode('ascii', 'ignore') if platform.system() == 'Windows' else str def file_size(file): diff --git a/utils/plots.py b/utils/plots.py index 7db527e14924..71e90b00241d 100644 --- a/utils/plots.py +++ b/utils/plots.py @@ -1,20 +1,19 @@ # Plotting utils +import math from copy import copy from pathlib import Path import cv2 -import math import matplotlib import matplotlib.pyplot as plt import numpy as np import pandas as pd import seaborn as sn import torch -import yaml from PIL import Image, ImageDraw, ImageFont -from utils.general import xywh2xyxy, xyxy2xywh +from utils.general import is_ascii, xyxy2xywh, xywh2xyxy from utils.metrics import fitness # Settings @@ -65,32 +64,31 @@ def butter_lowpass(cutoff, fs, order): return filtfilt(b, a, data) # forward-backward filter -def plot_one_box(x, im, color=(128, 128, 128), label=None, line_thickness=3): - # Plots one bounding box on image 'im' using OpenCV +def plot_one_box(box, im, color=(128, 128, 128), txt_color=(255, 255, 255), label=None, line_width=3, use_pil=False): + # Plots one xyxy box on image im with label assert im.data.contiguous, 'Image not contiguous. Apply np.ascontiguousarray(im) to plot_on_box() input image.' - tl = line_thickness or round(0.002 * (im.shape[0] + im.shape[1]) / 2) + 1 # line/font thickness - c1, c2 = (int(x[0]), int(x[1])), (int(x[2]), int(x[3])) - cv2.rectangle(im, c1, c2, color, thickness=tl, lineType=cv2.LINE_AA) - if label: - tf = max(tl - 1, 1) # font thickness - t_size = cv2.getTextSize(label, 0, fontScale=tl / 3, thickness=tf)[0] - c2 = c1[0] + t_size[0], c1[1] - t_size[1] - 3 - cv2.rectangle(im, c1, c2, color, -1, cv2.LINE_AA) # filled - cv2.putText(im, label, (c1[0], c1[1] - 2), 0, tl / 3, [225, 255, 255], thickness=tf, lineType=cv2.LINE_AA) - - -def plot_one_box_PIL(box, im, color=(128, 128, 128), label=None, line_thickness=3): - # Plots one bounding box on image 'im' using PIL - im = Image.fromarray(im) - draw = ImageDraw.Draw(im) - line_thickness = line_thickness or max(int(min(im.size) / 200), 2) - draw.rectangle(box, width=line_thickness, outline=color) # plot - if label: - font = ImageFont.truetype("Arial.ttf", size=max(round(max(im.size) / 40), 12)) - txt_width, txt_height = font.getsize(label) - draw.rectangle([box[0], box[1] - txt_height + 4, box[0] + txt_width, box[1]], fill=color) - draw.text((box[0], box[1] - txt_height + 1), label, fill=(255, 255, 255), font=font) - return np.asarray(im) + lw = line_width or max(int(min(im.size) / 200), 2) # line width + + if use_pil or not is_ascii(label): # use PIL + im = Image.fromarray(im) + draw = ImageDraw.Draw(im) + draw.rectangle(box, width=lw + 1, outline=color) # plot + if label: + font = ImageFont.truetype("Arial.ttf", size=max(round(max(im.size) / 40), 12)) + txt_width, txt_height = font.getsize(label) + draw.rectangle([box[0], box[1] - txt_height + 4, box[0] + txt_width, box[1]], fill=color) + draw.text((box[0], box[1] - txt_height + 1), label, fill=txt_color, font=font) + return np.asarray(im) + else: # use OpenCV + c1, c2 = (int(box[0]), int(box[1])), (int(box[2]), int(box[3])) + cv2.rectangle(im, c1, c2, color, thickness=lw, lineType=cv2.LINE_AA) + if label: + tf = max(lw - 1, 1) # font thickness + txt_width, txt_height = cv2.getTextSize(label, 0, fontScale=lw / 3, thickness=tf)[0] + c2 = c1[0] + txt_width, c1[1] - txt_height - 3 + cv2.rectangle(im, c1, c2, color, -1, cv2.LINE_AA) # filled + cv2.putText(im, label, (c1[0], c1[1] - 2), 0, lw / 3, txt_color, thickness=tf, lineType=cv2.LINE_AA) + return im def plot_wh_methods(): # from utils.plots import *; plot_wh_methods() @@ -180,7 +178,7 @@ def plot_images(images, targets, paths=None, fname='images.jpg', names=None, max cls = names[cls] if names else cls if labels or conf[j] > 0.25: # 0.25 conf thresh label = '%s' % cls if labels else '%s %.1f' % (cls, conf[j]) - plot_one_box(box, mosaic, label=label, color=color, line_thickness=tl) + mosaic = plot_one_box(box, mosaic, label=label, color=color, line_width=tl) # Draw image filename labels if paths: