🎨 [Update] progress and tqdm
Browse files- yolo/tools/log_helper.py +3 -3
- yolo/utils/dataloader.py +2 -1
yolo/tools/log_helper.py
CHANGED
@@ -47,7 +47,7 @@ class CustomProgress:
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self.wandb = wandb.init(project="YOLO", resume="allow", mode="online", dir="runs", name=cfg.name)
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def start_train(self, num_epochs: int):
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self.task_epoch = self.progress.add_task("[cyan]Epochs", total=num_epochs)
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def one_epoch(self):
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self.progress.update(self.task_epoch, advance=1)
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@@ -63,9 +63,9 @@ class CustomProgress:
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for loss_name, loss_value in loss_dict.items():
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self.wandb.log({f"Loss/{loss_name}": loss_value})
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loss_str = "
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for loss_name, loss_val in loss_dict.items():
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loss_str += f" {
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self.progress.update(self.batch_task, advance=1, description=f"[green]Batches [white]{loss_str}")
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self.wandb = wandb.init(project="YOLO", resume="allow", mode="online", dir="runs", name=cfg.name)
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def start_train(self, num_epochs: int):
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self.task_epoch = self.progress.add_task("[cyan]Epochs [white]| Loss | Box | DFL | BCE |", total=num_epochs)
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def one_epoch(self):
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self.progress.update(self.task_epoch, advance=1)
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for loss_name, loss_value in loss_dict.items():
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self.wandb.log({f"Loss/{loss_name}": loss_value})
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loss_str = "| -.-- |"
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for loss_name, loss_val in loss_dict.items():
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loss_str += f" {loss_val:2.2f} |"
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self.progress.update(self.batch_task, advance=1, description=f"[green]Batches [white]{loss_str}")
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yolo/utils/dataloader.py
CHANGED
@@ -7,6 +7,7 @@ import numpy as np
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import torch
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from loguru import logger
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from PIL import Image
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from torch.utils.data import DataLoader, Dataset
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from torchvision.transforms import functional as TF
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from tqdm.rich import tqdm
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@@ -74,7 +75,7 @@ class YoloDataset(Dataset):
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data = []
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valid_inputs = 0
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for image_name in
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if not image_name.lower().endswith((".jpg", ".jpeg", ".png")):
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continue
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image_id, _ = path.splitext(image_name)
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import torch
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from loguru import logger
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from PIL import Image
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from rich.progress import track
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from torch.utils.data import DataLoader, Dataset
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from torchvision.transforms import functional as TF
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from tqdm.rich import tqdm
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data = []
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valid_inputs = 0
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for image_name in track(images_list, description="Filtering data"):
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if not image_name.lower().endswith((".jpg", ".jpeg", ".png")):
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continue
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image_id, _ = path.splitext(image_name)
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