yolov5-fastapi-demo replace Chinese label

This chapter is based on the changes of the yolov5-fastapi-demo project

WelkinU/yolov5-fastapi-demo: FastAPI Wrapper of YOLOv5 (github.com)

First of all, because the labels set during training are in English, switching to Chinese requires retraining, and training in Chinese is cumbersome and requires many changes, so you can use English labels during training directly, and then make a judgment when recognizing drawings Just replace the label. as follows

if bbox["class_name"] =="Old English name":

       bbox["class_name"] = "New Chinese name"

In the plot_one_box of server.py, the label is the label passed in

Then after changing to a Chinese label, it turned out to be garbled characters? ? ? ?

It turns out that OpenCV does not support Chinese, so we change to draw.text to draw

First download the font package msyh

msyh.ttc font download-msyh.ttc download win10 compressed version-green resource network (downcc.com)

Drop it directly into the root directory

 Then import the package

from PIL import ImageFont, ImageDraw, Image

 Modify the content under the if label of plot_one_box:

    if label:
        tf = max(tl - 1, 1)  # font thickness
        t_size = cv2.getTextSize(label, 0, fontScale=tl / 3, thickness=tf)[0]
        font_size = t_size[1]
        font = ImageFont.truetype('msyh.ttc', font_size)
        t_size = font.getsize(label)
        c2 = c1[0] + t_size[0], c1[1] - t_size[1]
        cv2.rectangle(im, c1, c2, color, -1, cv2.LINE_AA)  # filled
        img_PIL = Image.fromarray(cv2.cvtColor(im, cv2.COLOR_BGR2RGB))
        draw = ImageDraw.Draw(img_PIL)
        draw.text((c1[0], c2[1] - 2), label, fill=(255, 255, 255), font=font)
        cv2.cvtColor(np.array(img_PIL), cv2.COLOR_RGB2BGR) 
        return cv2.cvtColor(np.array(img_PIL), cv2.COLOR_RGB2BGR)

At this point, the label has been successfully replaced with Chinese