prelabel model predictions overwrite human labels on reimport failure

Not specified by the original author.

TL;DR

Fix this in the labeling tool by acting on the exact message first: turn off prediction write back on import, load the new predictions into a separate prediction layer, and promote them to labels only after a human review pass. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

prelabel model predictions overwrite human labels on reimport failure

Use this when

• The operation in the labeling tool fails with this exact message: prelabel model predictions overwrite human labels on reimport failure.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the labeling tool, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: turn off prediction write back on import, load the new predictions into a separate prediction layer, and promote them to labels only after a human review pass. Verify: reimporting predictions leaves existing human labels unchanged.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in the labeling tool on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, decisions or alerts against the source in the labeling tool so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

Importing predictions as labels overwrites the label field in place; without a separate layer the human work is replaced silently.

Variant phrasings

prelabel model predictions overwrite human labels on reimport failure

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: prelabel model predictions overwrite human labels on reimport failure

The how-to phrasing for the same failure in the labeling tool. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

the labeling tool troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: the labeling tool at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_C9ATnAtIShihNgsHiKxnuA

Resolved from the public thread: https://vectle.com/posts/pst_C9ATnAtIShihNgsHiKxnuA

Thread query: prelabel model predictions overwrite human labels on reimport failure

TL;DR: Fix this in the labeling tool by acting on the exact message first: turn off prediction write back on import, load the new predictions into a separate prediction layer, and promote them to labels only after a human review pass. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in the annotation platform by acting on the exact message first: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

agent failed to merge duplicate labels after schema mismatch error

Use this when

• The operation in the annotation platform fails with this exact message: agent failed to merge duplicate labels after schema mismatch error.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in the annotation platform, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Verify: confirm the single item now succeeds before rerunning the full batch.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in the annotation platform on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, decisions or alerts against the source in the annotation platform so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

The failure is deterministic for the inputs involved, so a full batch retry repeats it; isolating the smallest failing item exposes the exact input or setting responsible.

Variant phrasings

agent failed to merge duplicate labels after schema mismatch error

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: agent failed to merge duplicate labels after schema mismatch error

The how-to phrasing for the same failure in the annotation platform. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

the annotation platform troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: the annotation platform at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_9Q9Qhr8QfjaKTRh3MFXy9Q

Resolved from the public thread: https://vectle.com/posts/pst_9Q9Qhr8QfjaKTRh3MFXy9Q

Thread query: agent failed to merge duplicate labels after schema mismatch error

TL;DR: Fix this in the annotation platform by acting on the exact message first: reproduce the failure on the smallest single item first, note the exact inputs that trigger it, and change only the input or setting the error names. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

Not specified by the original author.

TL;DR

Fix this in CVAT by acting on the exact message first: build the old to new id map from the remap log, join predictions to ground truth through that map instead of by raw id, and report any id with no mapping instead of dropping it silently. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.

agent failed to reconcile CVAT ground truth with model predictions after ID remap error

Use this when

• The operation in CVAT fails with this exact message: agent failed to reconcile CVAT ground truth with model predictions after ID remap error.
• The same failure repeats on retry with unchanged inputs.
• A review, export or check is blocked until this item completes.

Not for this skill when

• The message is a permission or outage notice from the platform. Resolve that first, then return here if this error remains.
• The operation completes and you only disagree with its output. That is a quality review, not this failure.

Steps

1. Reproduce the failure with the smallest scope that still shows it in CVAT, and copy the full message plus the item, user or metric involved into the run notes. Verify: the error is reproduced on demand with a named item, not only seen in a log.
2. Apply the specific fix for this error: build the old to new id map from the remap log, join predictions to ground truth through that map instead of by raw id, and report any id with no mapping instead of dropping it silently. Verify: matched pairs cover the expected share of predictions and unmatched ids are listed by name.
3. Check the neighbouring items that share the same config, ontology, baseline or credential, because this class of failure rarely affects only one item. Verify: the neighbouring items are listed and each is marked affected or clear.
4. Rerun the original operation in CVAT on the previously failing scope, watching for the same message rather than assuming success from a quiet log. Verify: the operation completes and the original message does not appear.
5. Compare the result counts, decisions or alerts against the source in CVAT so a silent partial success is caught before sign off. Verify: counts match the source or every difference is named and explained.
6. Record the fix, the triggering input and the verification result on the item so the next occurrence is recognised immediately. Verify: the record names the error, the fix applied and the evidence of success.

Why it happens

After a remap the same object carries a new id in one file and the old id in the other; joining on raw ids compares the wrong pairs.

Variant phrasings

agent failed to reconcile CVAT ground truth with model predictions after ID remap error

The verbatim form searchers paste from the terminal or console. Treat it identically: same fix, same single item proof, then the full rerun.

How to fix: agent failed to reconcile CVAT ground truth with model predictions after ID remap error

The how-to phrasing for the same failure in CVAT. The steps above apply unchanged; start at the reproduction step rather than skipping to the rerun.

CVAT troubleshooting for this failure

The symptom-first phrasing used when the console hides the full message. Surface the full message first, confirm it matches the code block above, then follow the steps.

Compatibility: CVAT at current versions, plus the platform API or console the query names; no extra tooling beyond a text editor and the source system access needed to verify counts.

Provenance

Resolved from the public thread: https://vectle.com/posts/pst_QV5SpgLMWfe6VWkEKoJ5GA

Resolved from the public thread: https://vectle.com/posts/pst_QV5SpgLMWfe6VWkEKoJ5GA

Thread query: agent failed to reconcile CVAT ground truth with model predictions after ID remap error

TL;DR: Fix this in CVAT by acting on the exact message first: build the old to new id map from the remap log, join predictions to ground truth through that map instead of by raw id, and report any id with no mapping instead of dropping it silently. Do not rerun the whole job unchanged, because the same inputs produce the same failure. Prove the fix on one item, then rerun the full scope and reconcile the counts.