BOTYW-0

> Provide more informations. Are you using matching model sizes for checkpoint and model declaration? Yes, i'm sure. I downloaded model Vitpose +-L form the wholebody dataset section, and I...

Thanks for your reply! I used the official website's code segmentation model before, but it also reported an error. I downloaded another model and successfully ran it using your segmentation...

Thanks for your reply! I used the offical code from [https://github.com/ViTAE-Transformer/ViTPose](url) for training. I can successfully run your inference code with other offical model.

For training, my model settings is model = dict( type='TopDown', pretrained=None, backbone=dict( type='ViT', img_size=(256, 192), patch_size=16, embed_dim=768, depth=12, num_heads=12, ratio=1, use_checkpoint=False, mlp_ratio=4, qkv_bias=True, drop_path_rate=0.3, ), keypoint_head=dict( type='TopdownHeatmapSimpleHead', in_channels=768, num_deconv_layers=0, num_deconv_filters=[],...

I solved this question: I add the `upsample=4` in the after model settings and in the topdown_heatmap_simple_head.py change the `if not isinstance(inputs, list): if self.upsample > 0: raise NotImplementedError return...