We lifted 5 functions out of this paper's own repositories and ran 4 of them in a sandbox. "Ran" means the function executed on a synthesized input and returned a value. It is not a reproduction of the paper's results.
| Repository | Role | Ran |
|---|---|---|
| EnVision-Research/Defect_Spectrum | canonical | 4 of 5 |
| Function | Status | Where it lives |
|---|---|---|
| get_first_five_images | Ran | EnVision-Research/Defect_Spectrum/dataset/image_datasets.py code served (permissive licence) · get_code("40369adbc7a4787e") |
| is_image_file | Ran | EnVision-Research/Defect_Spectrum/dataset/base_dataset.py code served (permissive licence) · get_code("6f527bbe13c81b60") |
| make_dataset | Ran | EnVision-Research/Defect_Spectrum/dataset/base_dataset.py code served (permissive licence) · get_code("35db53e6de24ca77") |
| normal_kl | Ran | EnVision-Research/Defect_Spectrum/models/distributions.py code served (permissive licence) · get_code("17eb0a31c91b671c") |
| extract | Not yet run | EnVision-Research/Defect_Spectrum/diffusion/base_diffusion.py code served (permissive licence) · get_code("07591fa9422585e7") |
Some links come from the archived Papers with Code dataset (CC BY-SA 4.0): attribution and licence.
Defect inspection is paramount within the closed-loop manufacturing system. However, existing datasets for defect inspection often lack precision and semantic granularity required for practical applications. In this paper, we introduce the Defect Spectrum, a comprehensive benchmark that offers precise, semantic-abundant, and large-scale annotations for a wide range of industrial defects. Building on four key industrial benchmarks, our dataset refines existing annotations and introduces rich semantic details, distinguishing multiple defect types within a single image. Furthermore, we introduce Defect-Gen, a two-stage diffusion-based generator designed to create high-quality and diverse defective images, even when working with limited datasets. The synthetic images generated by Defect-Gen significantly enhance the efficacy of defect inspection models. Overall, The Defect Spectrum dataset demonstrates its potential in defect inspection research, offering a solid platform for testing and refining advanced models.
The same record, over MCP at https://syntology.ai/mcp:
get_harvested_code_for_paper("2310.17316")
get_code_for_paper("2310.17316")
have("2310.17316")
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