Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Fix broken links in README.md #11060

Merged
merged 1 commit into from
Oct 20, 2023
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions README.md
Original file line number Diff line number Diff line change
Expand Up @@ -110,7 +110,7 @@ Apart from MMDetection, we also released [MMEngine](https://github.com/open-mmla
(2) Based on CO-DETR, MMDet released a model with a COCO performance of 64.1 mAP.
(3) Algorithms such as DINO support `AMP/Checkpoint/FrozenBN`, which can effectively reduce memory usage.

**2. [Comprehensive Performance Comparison between CNN and Transformer](<(projects/RF100-Benchmark/README.md)>)**
**2. [Comprehensive Performance Comparison between CNN and Transformer](projects/RF100-Benchmark/README.md)**
RF100 consists of a dataset collection of 100 real-world datasets, including 7 domains. It can be used to assess the performance differences of Transformer models like DINO and CNN-based algorithms under different scenarios and data volumes. Users can utilize this benchmark to quickly evaluate the robustness of their algorithms in various scenarios.

<div align=center>
Expand All @@ -130,7 +130,7 @@ We also provide a detailed process for training and evaluating Grounding DINO on
| Grounding DINO-R50 | R50 | Scratch | 48.9(+0.8) | 48.1 |

**4. Support for the open-vocabulary detection algorithm [Detic](projects/Detic_new/README.md) and multi-dataset joint training.**
**5. Training detection models using [FSDP and DeepSpeed](<(projects/example_largemodel/README.md)>).**
**5. Training detection models using [FSDP and DeepSpeed](projects/example_largemodel/README.md).**

| ID | AMP | GC of Backbone | GC of Encoder | FSDP | Peak Mem (GB) | Iter Time (s) |
| :-: | :-: | :------------: | :-----------: | :--: | :-----------: | :-----------: |
Expand Down