YOLO and ObjectClassifier fail silently on invalid or unreadable images

### Is there an existing issue for this?

- [x] I have searched the existing issues

### What happened?

## Bug Description
The YOLO and ObjectClassifier modules fail silently when an invalid or unreadable image file is provided.
When `cv2.imread()` returns `None`, the models previously returned empty results instead of raising a clear error.
This leads to confusing API behavior and makes debugging difficult.

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## Expected Behavior
When an invalid or unreadable image is provided:
- The API should return a structured **400 Bad Request** error.
- The frontend should receive a meaningful error message.
- Backend logs should clearly record the failure.
- Internal detection resources should be safely released.

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## Current Behavior
- `cv2.imread()` returns `None`
- No proper exception was raised earlier
- API returned empty results instead of an error
- Frontend receives misleading "no detections"
- Debugging becomes difficult

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## Proposed Fix
- Raise `HTTPException(status_code=400)` when the image is invalid/unreadable.
- Sanitize error messages to avoid exposing server file paths.
- Add consistent validation logic across YOLO and ObjectClassifier.
- Add unit tests to verify correct error handling.

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## Related Pull Request
Fix implemented in PR:
Fix: Standardize invalid image handling in YOLO and ObjectClassifier #679

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## Testing
- Valid image → YOLO and ObjectClassifier behave normally
- Corrupted image → API returns 400 Bad Request
- Missing file → Proper HTTPException raised

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## Labels
bug, backend, validation, tests, good first issue

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- [ ] Have you added unit tests?
- [ ] Have you made sure unit tests pass?
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