[Fix] Adapt YOLOv5 pipeline to handle models with dynamic HxW

[dbogunowicz]

YOLO Pipeline currently fails if the model has dynamic axis:
e.g.

(batch: "dynamic", channels: 3, height: "dynamic", width: "dynamic)

Testing

Raise value error if no image_size specified

from deepsparse import Pipeline

pipeline = Pipeline.create(model_path="zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none", task="yolo")
out = pipeline(images="src/deepsparse/yolo/sample_images/basilica.jpg")

out:

 File "/home/ubuntu/damian/deepsparse/src/deepsparse/yolo/pipelines.py", line 167, in setup_onnx_file_path
    raise ValueError(
ValueError: The model does not have a static image size shape. Specify the expected image size by passing the`image_size` argument to the pipeline.

Pass otherwise

from deepsparse import Pipeline

pipeline = Pipeline.create(model_path="zoo:cv/detection/yolov5-s/pytorch/ultralytics/coco/base-none", task="yolo", image_size=(320,320)
out = pipeline(images="src/deepsparse/yolo/sample_images/basilica.jpg")

Test with annotation pipeline

Behavior is consistent with Pipelines. The user need to specify the appropriate argument to specify the image size (will be notified about it by the appropriate error message)