Create README.md

README.md

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+import torch
+from huggingface_hub import hf_hub_download
+
+# Download the model file from Hugging Face Hub
+repo_name = "roughness_model"
+downloaded_file = hf_hub_download(
+    repo_id=f"Pra-tham/{repo_name}",  # Replace with your Hugging Face username
+    filename="roughness_model.pth"
+)
+print(f"Model downloaded from Hugging Face Hub: {downloaded_file}")
+
+
+
+# Initialize the model and load the state_dict
+
+model.load_state_dict(torch.load(downloaded_file))
+model.eval()  # Set to evaluation mode
+print("Model loaded successfully from Hugging Face Hub!")
+
+
+# Set the computation device
+device0 = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+
+# Load the pretrained model checkpoint
+load_path = "/kaggle/working/metric_depth_vit_large_800k.pth"
+checkpoint = torch.load(load_path, map_location="cpu")
+
+# Load the model configuration
+cfg_large = Config.fromfile('/kaggle/working/Texture_training/training/mono/configs/RAFTDecoder/vit.raft5.large.py')
+
+# Initialize the DepthModel
+model = DepthModel(cfg_large, None)
+
+# Load the model's state dictionary
+ckpt_state_dict = checkpoint['model_state_dict']
+model.load_state_dict(ckpt_state_dict, strict=False)
+
+# Print the model architecture
+#print(model)