YOLOv8-16bit/docs/predict.md

Inference or prediction of a task returns a list of Results objects. Alternatively, in the streaming mode, it returns a generator of Results objects which is memory efficient. Streaming mode can be enabled by passing stream=True in predictor's call method.

!!! example "Predict" === "Getting a List" python inputs = [img, img] # list of np arrays results = model(inputs) # List of Results objects for result in results: boxes = results.boxes # Boxes object for bbox outputs masks = results.masks # Masks object for segmenation masks outputs probs = results.probs # Class probabilities for classification outputs ... === "Getting a Generator" python inputs = [img, img] # list of np arrays results = model(inputs, stream=True) # Generator of Results objects for result in results: boxes = results.boxes # Boxes object for bbox outputs masks = results.masks # Masks object for segmenation masks outputs probs = results.probs # Class probabilities for classification outputs ...

Working with Results

Results object consists of these component objects:

• results.boxes : It is an object of class Boxes. It has properties and methods for manipulating bboxes
• results.masks : It is an object of class Masks. It can be used to index masks or to get segment coordinates.
• results.prob : It is a Tensor object. It contains the class probabilities/logits.

Each result is composed of torch.Tensor by default, in which you can easily use following functionality:

results = results.cuda()
results = results.cpu()
results = results.to("cpu")
results = results.numpy()

Boxes

Boxes object can be used index, manipulate and convert bboxes to different formats. The box format conversion operations are cached, which means they're only calculated once per object and those values are reused for future calls.

• Indexing a Boxes objects returns a Boxes object

boxes = results.boxes
box = boxes[0] # returns one box
box.xyxy 

• Properties and conversions

results.boxes.xyxy   # box with xyxy format, (N, 4)
results.boxes.xywh   # box with xywh format, (N, 4)
results.boxes.xyxyn  # box with xyxy format but normalized, (N, 4)
results.boxes.xywhn  # box with xywh format but normalized, (N, 4)
results.boxes.conf   # confidence score, (N, 1)
results.boxes.cls    # cls, (N, 1)

Masks

Masks object can be used index, manipulate and convert masks to segments. The segment conversion operation is cached.

results.masks.masks     # masks, (N, H, W)
results.masks.segments  # bounding coordinates of masks, List[segment] * N

probs

probs attribute of Results class is a Tensor containing class probabilities of a classification operation.

results.probs     # cls prob, (num_class, )

Class reference documentation for Results module and its components can be found here