python进度条组件

python 进度条组件

作者：elfin  资料来源：原创

目录

• 1、在循环体中加入进度条

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1、在循环体中加入进度条

def save_txt(d, save_json="Data/train/"):
    my_bar1 = tqdm(d["annotations"])
    for ann in my_bar1:
        my_bar1.set_description("annotations handle: ")
        image_id = ann.get("image_id")

        # 若不存在image_id就放弃此条数据
        if type(image_id) != int:
            continue
        # 将annotations的数据整合成：{"img_id": [ann, ……]}的形式
        if res.get(f"{image_id}"):
            res[f"{image_id}"].append(ann)
        else:
            res[f"{image_id}"] = []
            res[f"{image_id}"].append(ann)

    # 撰写最后的标注数据，形成{"filename": [ann, ……]}, 中间通过image_id进行对应
    my_bar2 = tqdm(d["images"])
    for img in my_bar2:
        my_bar2.set_description("Images_id filename >>> ")
        # 若当前image本身就包含了标注数据，则将这些
        if img.get("annotations"):
            label_name = img.get("file_name").split(".")[0]
            result[f"{label_name}"] = {
                "annotations": img.get("annotations"),
                "width": img.get("width"),
                "height": img.get("height")
            }
        else:
            img_id = img.get("id")
            if res.get(str(img_id)):
                label_name = img.get("file_name").split(".")[0]
                result[f"{label_name}"] = {
                    "annotations": res.get(str(img_id)),
                    "width": img.get("width"),
                    "height": img.get("height")
                }

    # 判断保存路径是否存在
    if not os.path.exists(PROJECT_DIR + save_json):
        os.makedirs(PROJECT_DIR + save_json)
    with open(PROJECT_DIR + save_json + "train_modify.json", "w+") as f2:
        json.dump(res, f2, indent=4,
                  sort_keys=True, ensure_ascii=False)
        f2.close()

pycharm显示的进度条：

annotations handle: : 100%|██████████| 3263046/3263046 [02:19<00:00, 23418.42it/s]
Images_id filename >>> : 100%|██████████| 335703/335703 [00:14<00:00, 23051.71it/s]

这里我们设置了进度条的样式，在实际应用中可以加入自己想展示的关键信息。如模型训练中加入损失：

import time
from tqdm import tqdm

batches = [[1, 2, 3], [1, 2, 3], [1, 2, 3], [1, 2, 3]]
my_bar = tqdm(batches)
batch_num = 0
for i in my_bar:
    loss = 2 * (1 / (1 + batch_num)**2)
    my_bar.set_description(f"epoch:{batch_num+1}/{len(batches)}	total_loss: {loss}	")
    batch_num += 1
    time.sleep(1)

pycharm显示的进度条：

epoch:4/4	total_loss: 0.125	: 100%|██████████| 4/4 [00:04<00:00,  1.00s/it]