Comments (1)
Hi and thanks for your interest in using DINOv2! No, all the visual tasks on which we had evaluation results are listed in paper and we haven't tried (yet) OCR / text recognition tasks. But if you try, please share back your experience.
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Related Issues (20)
- Run vanilla DinoV2 training with unlabelled dataset to fit specific field data HOT 1
- why do Self-supervised image retrieval? HOT 1
- Can you release the weight of dino head and ibot head๏ผ HOT 2
- Resume training from intermediate checkpoint? HOT 1
- Why is total_iters unrelated to batch size and number of data? HOT 2
- ResNet50 architecture HOT 1
- Train depth / segmentation head HOT 1
- Implementation using ytorch lightning
- Drop path implementation
- Do black borders affect model performance? HOT 4
- run code at about [ 3170/125000], [W CudaIPCTypes.cpp:16] Producer process has been terminated before all shared CUDA tensors released. See Note [Sharing CUDA tensors]
- Memory-efficient attention forward operator error in Docker container with FastAPI and DINOv2 HOT 9
- torchrun --nproc_per_node=4 /data/zxb/DINO_FL/train/train.py HOT 2
- Fine-Tuning ViT backbone for Depth Estimation
- Upload 3D Ct Scans into Dinov2
- Patch to support torch version > 2.1 and running using torchrun
- Docker multi-architecture build issues for DINOv2 API on AWS and Mac
- Get visualization of the three first principal components HOT 1
- Loss doesn't go down.
- Is it possible to Use DINOv2 for Facial Recognition/Search HOT 1
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