System Info

• transformers version: 4.41.2
• Platform: Linux-5.4.0-182-generic-x86_64-with-glibc2.31
• Python version: 3.11.8
• Huggingface_hub version: 0.23.0
• Safetensors version: 0.4.2
• Accelerate version: 0.30.1
• Accelerate config: not found
• PyTorch version (GPU?): 2.2.2+cu121 (True)
• Tensorflow version (GPU?): not installed (NA)
• Flax version (CPU?/GPU?/TPU?): not installed (NA)
• Jax version: not installed
• JaxLib version: not installed
• Using GPU in script?:
• Using distributed or parallel set-up in script?:

When running the ObjectDetectionPipeline in a batch, the output will only be the bounding boxes of the first input image due to ObjectDetectionPipeline.py accessing element [0] in postprocessing and not looping over all outputs.

This accesses only and always the first element, instead of looping over all outputs.

Only the first element is accessed in postprocessing

Who can help?

@Narsil

Information

• The official example scripts
• My own modified scripts

Tasks

• An officially supported task in the examples folder (such as GLUE/SQuAD, ...)
• My own task or dataset (give details below)

Reproduction

1. Create object detection Pipeline

pipe = pipeline("object-detection", model=model_name, image_processor=preprocessor_name, device=device)

2. use batch inference with batch_size > 2.
   for out in tqdm(pipe(dataset, batch_size=batch_size)):

Expected behavior

Expected Output: 2 Elements with each x items (bboxes).
Actual Output, only bboxes of the first input element.