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PP OCRv6 Medium Det Mlx

This is an MLX-format conversion of PaddlePaddle/PP-OCRv6mediumdetsafetensors for use with mlx-vlm.

Sourcehuggingface.co/mikoy92/PP-OCRv6-medium-det-mlx/tree/364560d8396a9acfe691a4aa54d090bc4a3663f3
TypeOtherModèle de basePaddlePaddle/PP-OCRv6_medium_det_safetensorsVersionRevision 364560dBClasse

Source du modèle

Type
Other
Taille du fichier
83,9 MB
Modèle de base
PaddlePaddle/PP-OCRv6_medium_det_safetensors
Version
vRevision 364560d
Mis à jour
23 oct. 2026
Téléchargements
31
Source
Hugging Face

Description de la source

PP-OCRv6 medium text detection MLX

This is an MLX-format conversion of PaddlePaddle/PP-OCRv6_medium_det_safetensors for use with mlx-vlm.

import mlx.core as mx
from PIL import Image
from mlx_vlm import load

model, processor = load("mikoy92/PP-OCRv6-medium-det-mlx")
image = Image.open("document.png")

inputs = processor(image)
outputs = model(**inputs)
mx.eval(outputs.logits)

result = processor.post_process_object_detection(
    outputs,
    target_sizes=inputs["target_sizes"],
)[0]
print(result["boxes"])

Sources

1 source
Hugging FacePrincipalVersion 364560d8396a9acfe691a4aa54d090bc4a3663f3
huggingface.co/mikoy92/PP-OCRv6-medium-det-mlx/tree/364560d8396a9acfe691a4aa54d090bc4a3663f3

Vérifié 23 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 83,9 MB · SHA-256 4529347f25cf…6349 · Hugging Face

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Extraits de sources

3 extraits
Readme6 aoûthuggingface.co/mikoy92/PP-OCRv6-medium-det-mlx

--- license: apache-2.0 library_name: mlx language: - en - zh pipeline_tag: image-to-text tags: - OCR - PaddlePaddle - PaddleOCR - textline_detection - mlx base_model: PaddlePaddle/PP-OCRv6_medium_det_safetensors --- # PP-OCRv6 medium text detection MLX This is an MLX-format conversion of `PaddlePaddle/PP-OCRv6_medium_det_safetensors` for use with `mlx-vlm`. ```python import mlx.core as mx from PIL import Image from mlx_vlm import load model, processor = load("mikoy92/PP-OCRv6-medium-det-mlx") image = Image.open("document.png") inputs = processor(image) outputs = model(**inputs) mx.eval(outputs.logits) result = processor.post_process_object_detection( outputs, target_sizes=inputs["target_sizes"], )[0] print(result["boxes"]) ```

Note23 oct.huggingface.co/mikoy92/PP-OCRv6-medium-det-mlx

Source context: 31 downloads · 0 likes · Pipeline image-to-text · Library mlx · Repo mikoy92/PP-OCRv6-medium-det-mlx

Note6 aoûthuggingface.co/mikoy92/PP-OCRv6-medium-det-mlx

Source context: 102 downloads · 0 likes · Pipeline image-to-text · Library mlx · Repo mikoy92/PP-OCRv6-medium-det-mlx