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kaushik3009/industrial-vision-agent
industrial-vision-agent is a machine learning model from kaushik3009. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for pytorch. The card lists the license as mit.
Trained checkpoints for an agentic multimodal quality-inspection system on metal castings (7,347 images, binary defect classification + weakly-supervised segmentation).
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Updated Aug 25, 2026
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From the Hugging Face model README
Trained checkpoints for an agentic multimodal quality-inspection system on metal castings (7,347 images, binary defect classification + weakly-supervised segmentation).
| File | Architecture | Role | Verified metric |
|---|---|---|---|
vit_tiny_patch16_224_best.pth | ViT-Tiny (timm), fine-tuned | Defect classifier | Test F1 0.9967 / Recall 0.9956 |
resnet18_best.pth | ResNet18, linear-probed head | Grad-CAM localization backbone | Test F1 0.924 |
mobilenetv3_small_050_best.pth | MobileNetV3-small distilled student | Edge classifier (94.9% fewer params) | Test F1 0.991 |
unet_pseudo_best.pth | U-Net trained on Grad-CAM pseudo-masks | Segmentation (224x224 mask) | Val Dice 0.706 |
metrics.json | — | Full training/test results | — |
INT8 dynamic quantization of the ViT shrinks it 71.7% (22.2 -> 6.3 MB).
import torch, timm
from huggingface_hub import hf_hub_download
weights = hf_hub_download("kaushik3009/industrial-vision-agent", "vit_tiny_patch16_224_best.pth")
model = timm.create_model("vit_tiny_patch16_224", pretrained=False, num_classes=2)
model.load_state_dict(torch.load(weights, map_location="cpu"))
Labels: 0 = OK, 1 = Defective. Input: RGB, resized 224x224, ImageNet-normalized.
Full pipeline, agent code, and docs: https://github.com/kaushik-3009/industrial-vision-agent