Product Image Annotation Needed

I need a detail-oriented freelancer to annotate a new set of product images. The core task is image annotation: drawing precise bounding boxes (or polygons, where relevant), assigning the correct product class label, and flagging any occlusions or quality issues so the final dataset is clean and ready for model training.

Although the main focus is on product images, there is a small companion set of customer-written snippets that also need sentiment analysis tags. If you already have experience combining visual labels with text annotations, that will be a plus.

What I’m looking for:
• Consistent, pixel-accurate image annotation following the guidelines I will provide.
• Proper file structure and export in COCO JSON or Pascal VOC XML (I’ll confirm which once we start).
• Basic sentiment analysis on short text segments, labeled as positive, neutral, or negative according to my template.
• Clear communication whenever a guideline seems ambiguous; I prefer to resolve questions early.
• On-time delivery—quality is crucial, but I also have a firm deadline to meet.

Tools: I’m flexible—Labelbox, CVAT, VGG Image Annotator, or a comparable platform is fine, as long as the output format matches the requirements above.

To help me gauge fit, please mention:
1. The annotation tool you prefer and why.
2. Rough turn-around time for annotating 100 product images.
3. Any prior projects where you balanced image annotation with sentiment analysis (if applicable).

I’ll share a small pilot batch first; if the quality and speed are right, we can expand to the full dataset. Looking forward to working together on a clean, reliable annotation pipeline.