Error code:   JWTInvalidSignature
Exception:    InvalidSignatureError
Message:      Signature verification failed
Traceback:    Traceback (most recent call last):
                File "/src/libs/libapi/src/libapi/jwt_token.py", line 286, in validate_jwt
                  decoded = jwt.decode(
                      jwt=token,
                  ...<2 lines>...
                      options=options,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 368, in decode
                  decoded = self.decode_complete(
                      jwt,
                  ...<8 lines>...
                      leeway=leeway,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jwt.py", line 265, in decode_complete
                  decoded = self._jws.decode_complete(
                      jwt,
                  ...<3 lines>...
                      detached_payload=detached_payload,
                  )
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 270, in decode_complete
                  self._verify_signature(
                  ~~~~~~~~~~~~~~~~~~~~~~^
                      signing_input,
                      ^^^^^^^^^^^^^^
                  ...<4 lines>...
                      options=merged_options,
                      ^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/usr/local/lib/python3.14/site-packages/jwt/api_jws.py", line 417, in _verify_signature
                  raise InvalidSignatureError("Signature verification failed")
              jwt.exceptions.InvalidSignatureError: Signature verification failed

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Welding Defect Object Detection

2,028 annotated images of welds for defect detection, in both YOLO and COCO formats. Three classes:

id (YOLO / COCO)	name
0 / 1	Bad Weld
1 / 2	Good Weld
2 / 3	Defect

Splits

split	images	annotations
train	1,619	4,583
valid	283	802
test	126	301

Layout

├── data.yaml            # YOLO class names + split paths
├── train|valid|test/
│   ├── images/          # .jpg
│   └── labels/          # YOLO .txt (class cx cy w h, normalized)
└── coco/
    ├── train.json       # COCO detection format
    ├── valid.json
    └── test.json

COCO conversion notes

The coco/ jsons were generated from the YOLO labels with the flux YOLO→COCO converter:

bbox = [x_min, y_min, width, height], float pixels
boxes clamped to image bounds
category ids are one-based (YOLO class 0 → COCO id 1)
annotation count parity verified: 5,686 YOLO label lines → 5,686 COCO annotations

Source & license

Original dataset published on Kaggle by sukmaadhiwijaya as Welding Defect - Object Detection under CC0: Public Domain. This mirror adds the COCO-format annotations.

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Total file size:

104 MB