---
title: "Pixeltable vs Voxel51 (FiftyOne): production tables vs the dataset App"
description: "FiftyOne wins visualization and CV eval. Pixeltable wins incremental production tables. Export with pxt.io.export_images_as_fo_dataset. Not a replacement fight."
keywords:
  - Pixeltable vs Voxel51
  - FiftyOne alternative
  - computer vision dataset
  - multimodal AI infrastructure
  - model evaluation
url: "https://pixeltable.com/compare/pixeltable-vs-voxel51"
---

# Pixeltable vs Voxel51 (FiftyOne)

FiftyOne is eyes on the dataset: the App, zoo models, COCO-style evaluation, plugins. Pixeltable is the production table: incremental inference, versioning, serving. Explore in FiftyOne. Produce in Pixeltable. Export with pxt.io.export_images_as_fo_dataset.

## Summary

### Pixeltable

- Image and video tables with computed model columns
- Insert runs inference; only new rows recompute
- HTTP from the same file if you declare it
- No FiftyOne App, no zoo, no evaluate_detections

### Voxel51 (FiftyOne)

- Interactive App for embeddings, mistakes, and slices
- Model zoo, plugins, 3D / video / audio samples
- evaluate_detections and dataset curation workflows
- Not an application backend or embedding-index-as-schema

## Comparison

| Feature | Pixeltable | Voxel51 (FiftyOne) |
| --- | --- | --- |
| Job | Production tables, incremental compute, serving | Dataset visualization, curation, and CV eval |
| Looking at the data | pxt dashboard and queries; not a CV visualizer | FiftyOne App — this is why people open it |
| Model eval | Computed columns and aggregates you write | evaluate_detections, zoo models, mistake views |
| Incremental production | Computed columns on insert; lineage in the catalog | Apply a model to a dataset; you re-run when the set changes |
| Modalities | Image, Video, Audio, Document, Json in one schema | Images, video, 3D, audio, and plugins — not a “CV-only leftover” |
| Join | pxt.io.export_images_as_fo_dataset | Load the exported Dataset and launch_app |

## Produce, then look

Pixeltable runs DETR on insert and exports a FiftyOne dataset. FiftyOne loads a zoo set, applies a model, and opens the App. Apply Pixeltable with pxt schema update app.py cv.

### Pixeltable

```python
import fiftyone as fo
import pixeltable as pxt
from pixeltable.functions.huggingface import detr_for_object_detection

TableModel = pxt.model_base()

class Images(TableModel, name='images'):
    image: pxt.Image
    detections = detr_for_object_detection(
        image, model_id='facebook/detr-resnet-50'
    )

# pxt schema update app.py cv
images = pxt.get_table('cv.images')
images.insert([{'image': 'frame.jpg'}])

@pxt.udf
def detr_to_fo(img: pxt.Image, detr_labels: dict) -> list:
    boxes = []
    for label, box, score in zip(
        detr_labels['label_text'],
        detr_labels['boxes'],
        detr_labels['scores'],
    ):
        x1, y1, x2, y2 = box
        boxes.append({
            'label': label,
            'confidence': score,
            'bounding_box': [
                x1 / img.width,
                y1 / img.height,
                (x2 - x1) / img.width,
                (y2 - y1) / img.height,
            ],
        })
    return boxes

fo_dataset = pxt.io.export_images_as_fo_dataset(
    images,
    images.image,
    detections=detr_to_fo(images.image, images.detections),
)
session = fo.launch_app(fo_dataset)
```

### Voxel51 (FiftyOne)

```python
import fiftyone as fo
import fiftyone.zoo as foz
from fiftyone import ViewField as F

dataset = foz.load_zoo_dataset('quickstart')
model = foz.load_zoo_model('yolov5s-coco-torch')
dataset.apply_model(model, label_field='predictions')
session = fo.launch_app(dataset)

results = dataset.evaluate_detections(
    'predictions',
    gt_field='ground_truth',
    eval_key='eval',
)
high_precision = dataset.match(F('eval.precision') > 0.8)
high_precision.export(export_dir='./curated')
# Pixeltable does not ship this App or evaluate_detections.
```

## When to choose Pixeltable

- **The table is the product**: New images should run the model without a notebook re-apply. You need versioning, HTTP, or an embedding index on production rows.
- **You already curate in FiftyOne**: Keep the App. Export from Pixeltable when you want eyes on model output. Howto: docs.pixeltable.com/howto/working-with-fiftyone

## When to choose Voxel51 (FiftyOne)

- **You need to see the dataset**: Embeddings projector, mistake slices, plugins. Pixeltable dashboard is not a substitute.
- **CV eval is the job this week**: Zoo models, evaluate_detections, COCO-style metrics. Do not migrate off FiftyOne for that.

## FAQ

### Is Pixeltable a FiftyOne alternative?

No as a visualizer or CV eval suite. Yes as the production table those curated samples feed. Teams often use both.

### Can Pixeltable replace the FiftyOne App?

No. That is the honest loss. Export into FiftyOne when you need the App.

### Does FiftyOne only do images and video?

No. Current FiftyOne includes 3D, audio, and plugins. This page used to say “limited multimodal”; that was wrong.