More stock photos fromValeriy Kirsanov's portfolio Related categories AnimalsInsects Browse categories Abstract Arts & Architecture Business Editorial Holidays IT & C Illustrations & Clipart Industries Nature Objects People Technology Travel Web Design Graphics...
python -m torch.distributed.launch --nproc_per_node=8 main.py \ --model hornet_tiny_7x7 --drop_path 0.2 --clip_grad 5\ --batch_size 128 --lr 4e-3 --update_freq 4 \ --model_ema true --model_ema_eval true \ --data_path /path/to/imagenet-1k \ --output_dir ./logs/hornet...
The hornet attacks Hornet en face Wasp Wasp Related categories AnimalsInsects Browse categories Abstract Arts & Architecture Business Editorial Holidays IT & C Illustrations & Clipart Industries Nature Objects People Technology Travel Web Design Graphics...
ResNest50() img = test_images.dog() superimposed_img, heatmap, preds = visualizing.make_and_apply_gradcam_heatmap(mm, img, layer_name="auto") plot_attention_score_maps is model attention score maps visualization. from keras_cv_attention_models import visualizing, test_images, botnet img ...
# Exported simplified onnx: convnext_tiny.onnx # Onnx run test tt = imagenet.eval_func.ONNXModelInterf('convnext_tiny.onnx') print(mm.decode_predictions(tt(mm.preprocess_input(test_images.cat())) # [[('n02124075', 'Egyptian_cat', 0.880507), ('n02123045', 'tabby', 0.0047998047...
os.environ["KECAM_BACKEND"] = "torch" from keras_cv_attention_models import convnext, test_images, imagenet # >>> Using PyTorch backend mm = convnext.ConvNeXtTiny() mm.export_onnx(simplify=True) # Exported onnx: convnext_tiny.onnx # Running onnxsim.simplify... # Exported simplified...