New YOLOv5 Classification Models (#8956)

* Update * Logger step fix: Increment step with epochs (#8654) * enhance * revert * allow training from scratch * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update --img argument from train.py single line * fix image size from 640 to 128 * suport custom dataloader and augmentation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * format * Update dataloaders.py * Single line return, single line comment, remove unused argument * address PR comments * fix spelling * don't augment eval set * use fstring * update augmentations.py * new maning convention for transforms * reverse if statement, inline ops * reverse if statement, inline ops * updates * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update dataloaders * Remove additional if statement * Remove is_train as redundant * Cleanup * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Cleanup2 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update classifier.py * Update augmentations.py * fix: imshow clip warning * update * Revert ToTensorV2 removal * Update classifier.py * Update normalize values, revert uint8 * normalize image using cv2 * remove dedundant comment * Update classifier.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * replace print with logger * commit steps * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Allow logging models from GenericLogger (#8676) * enhance * revert * allow training from scratch * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update --img argument from train.py single line * fix image size from 640 to 128 * suport custom dataloader and augmentation * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * format * Update dataloaders.py * Single line return, single line comment, remove unused argument * address PR comments * fix spelling * don't augment eval set * use fstring * update augmentations.py * new maning convention for transforms * reverse if statement, inline ops * reverse if statement, inline ops * updates * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update dataloaders * Remove additional if statement * Remove is_train as redundant * Cleanup * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Cleanup2 * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update classifier.py * Update augmentations.py * fix: imshow clip warning * update * Revert ToTensorV2 removal * Update classifier.py * Update normalize values, revert uint8 * normalize image using cv2 * remove dedundant comment * Update classifier.py * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * replace print with logger * commit steps * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * support final model logging * update * update * update * update * remove curses * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update classifier.py * Update __init__.py Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com> * Update * Update * Update * Update * Update dataset download * Update dataset download * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Pass imgsz to classify_transforms() * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Update * Cos scheduler * Cos scheduler * Remove unused args * Update * Add seed * Add seed * Update * Update * Add run(), main() * Merge master * Merge master * Update * Update * Update * Update * Update * Update * Update * Create YOLOv5 BaseModel class (#8829) * Create BaseModel * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * fix * Hub load device fix * Update Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> * Add experiment * Merge master * Attach names * weight decay = 1e-4 * weight decay = 5e-5 * update smart_optimizer console printout * fashion-mnist fix * Merge master * Update Table * Update Table * Remove destroy process group * add kwargs to forward() * fuse fix for resnet50 * nc, names fix for resnet50 * nc, names fix for resnet50 * ONNX CPU inference fix * revert * cuda * if augment or visualize * if augment or visualize * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * New smart_inference_mode() * Update README * Refactor into /classify dir * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * reset defaults * reset defaults * fix gpu predict * warmup * ema half fix * spacing * remove data * remove cache * remove denormalize * save run settings * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * verbose false on initial plots * new save_yaml() function * Update ci-testing.yml * Path(data) CI fix * Separate classification CI * fix val * fix val * fix val * smartCrossEntropyLoss * skip validation on hub load * autodownload with working dir root * str(data) * Dataset usage example * im_show normalize * im_show normalize * add imagenet simple names to multibackend * Add validation speeds * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * 24-space names * Update bash scripts * Update permissions * Add bash script arguments * remove verbose * TRT data fix * names generator fix * optimize if names * update usage * Add local loading * Verbose=False * update names printing * Add Usage examples * Add Usage examples * Add Usage examples * Add Usage examples * named_children * reshape_classifier_outputs * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * update * update * fix CI * fix incorrect class substitution * fix incorrect class substitution * remove denormalize * ravel fix * cleanup * update opt file printing * update opt file printing * update defaults * add opt to checkpoint * Add warning * Add comment * plot half bug fix * Use NotImplementedError * fix export shape report * Fix TRT load * cleanup CI * profile comment * CI fix * Add cls models * avoid inplace error * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Fix usage examples * Update README * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README * Update README Co-authored-by: Ayush Chaurasia <ayush.chaurarsia@gmail.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
2022-08-17 11:59:01 +02:00
1 parent 3456fe65c6
commit d3ea0df8b9
@@ -5,6 +5,7 @@ Logging utils

 import os
 import warnings
+from pathlib import Path

 import pkg_resources as pkg
 import torch
@@ -76,7 +77,7 @@ class Loggers():
            self.logger.info(s)
        if not clearml:
            prefix = colorstr('ClearML: ')
-            s = f"{prefix}run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 runs in ClearML"
+            s = f"{prefix}run 'pip install clearml' to automatically track, visualize and remotely train YOLOv5 🚀 in ClearML"
            self.logger.info(s)

        # TensorBoard
@@ -121,11 +122,8 @@ class Loggers():
        # Callback runs on train batch end
        # ni: number integrated batches (since train start)
        if plots:
-            if ni == 0:
-                if self.tb and not self.opt.sync_bn:  # --sync known issue https://github.com/ultralytics/yolov5/issues/3754
-                    with warnings.catch_warnings():
-                        warnings.simplefilter('ignore')  # suppress jit trace warning
-                        self.tb.add_graph(torch.jit.trace(de_parallel(model), imgs[0:1], strict=False), [])
+            if ni == 0 and not self.opt.sync_bn and self.tb:
+                log_tensorboard_graph(self.tb, model, imgsz=list(imgs.shape[2:4]))
            if ni < 3:
                f = self.save_dir / f'train_batch{ni}.jpg'  # filename
                plot_images(imgs, targets, paths, f)
@@ -233,3 +231,78 @@ class Loggers():
        # params: A dict containing {param: value} pairs
        if self.wandb:
            self.wandb.wandb_run.config.update(params, allow_val_change=True)
+
+
+class GenericLogger:
+    """
+    YOLOv5 General purpose logger for non-task specific logging
+    Usage: from utils.loggers import GenericLogger; logger = GenericLogger(...)
+    Arguments
+        opt:             Run arguments
+        console_logger:  Console logger
+        include:         loggers to include
+    """
+
+    def __init__(self, opt, console_logger, include=('tb', 'wandb')):
+        # init default loggers
+        self.save_dir = opt.save_dir
+        self.include = include
+        self.console_logger = console_logger
+        if 'tb' in self.include:
+            prefix = colorstr('TensorBoard: ')
+            self.console_logger.info(
+                f"{prefix}Start with 'tensorboard --logdir {self.save_dir.parent}', view at http://localhost:6006/")
+            self.tb = SummaryWriter(str(self.save_dir))
+
+        if wandb and 'wandb' in self.include:
+            self.wandb = wandb.init(project="YOLOv5-Classifier" if opt.project == "runs/train" else opt.project,
+                                    name=None if opt.name == "exp" else opt.name,
+                                    config=opt)
+        else:
+            self.wandb = None
+
+    def log_metrics(self, metrics_dict, epoch):
+        # Log metrics dictionary to all loggers
+        if self.tb:
+            for k, v in metrics_dict.items():
+                self.tb.add_scalar(k, v, epoch)
+
+        if self.wandb:
+            self.wandb.log(metrics_dict, step=epoch)
+
+    def log_images(self, files, name='Images', epoch=0):
+        # Log images to all loggers
+        files = [Path(f) for f in (files if isinstance(files, (tuple, list)) else [files])]  # to Path
+        files = [f for f in files if f.exists()]  # filter by exists
+
+        if self.tb:
+            for f in files:
+                self.tb.add_image(f.stem, cv2.imread(str(f))[..., ::-1], epoch, dataformats='HWC')
+
+        if self.wandb:
+            self.wandb.log({name: [wandb.Image(str(f), caption=f.name) for f in files]}, step=epoch)
+
+    def log_graph(self, model, imgsz=(640, 640)):
+        # Log model graph to all loggers
+        if self.tb:
+            log_tensorboard_graph(self.tb, model, imgsz)
+
+    def log_model(self, model_path, epoch=0, metadata={}):
+        # Log model to all loggers
+        if self.wandb:
+            art = wandb.Artifact(name=f"run_{wandb.run.id}_model", type="model", metadata=metadata)
+            art.add_file(str(model_path))
+            wandb.log_artifact(art)
+
+
+def log_tensorboard_graph(tb, model, imgsz=(640, 640)):
+    # Log model graph to TensorBoard
+    try:
+        p = next(model.parameters())  # for device, type
+        imgsz = (imgsz, imgsz) if isinstance(imgsz, int) else imgsz  # expand
+        im = torch.zeros((1, 3, *imgsz)).to(p.device).type_as(p)  # input image
+        with warnings.catch_warnings():
+            warnings.simplefilter('ignore')  # suppress jit trace warning
+            tb.add_graph(torch.jit.trace(de_parallel(model), im, strict=False), [])
+    except Exception:
+        print('WARNING: TensorBoard graph visualization failure')