Detect.py supports running against a Triton container (#9228)

* update coco128-seg comments

* Enables detect.py to use Triton for inference

Triton Inference Server is an open source inference serving software
that streamlines AI inferencing.
https://github.com/triton-inference-server/server

The user can now provide a "--triton-url" argument to detect.py to use
a local or remote Triton server for inference.
For e.g., http://localhost:8000 will use http over port 8000
and grpc://localhost:8001 will use grpc over port 8001.
Note, it is not necessary to specify a weights file to use Triton.

A Triton container can be created by first exporting the Yolov5 model
to a Triton supported runtime. Onnx, Torchscript, TensorRT are
supported by both Triton and the export.py script.

The exported model can then be containerized via the OctoML CLI.
See https://github.com/octoml/octo-cli#getting-started for a guide.

* added triton client to requirements

* fixed support for TFSavedModels in Triton

* reverted change

* Test CoreML update

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update ci-testing.yml

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Use pathlib

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Refacto DetectMultiBackend to directly accept triton url as --weights http://...

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Deploy category

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update detect.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update common.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update common.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update predict.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update predict.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update predict.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update triton.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* Update triton.py

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Add printout and requirements check

* Cleanup

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>

* triton fixes

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* fixed triton model query over grpc

* Update check_requirements('tritonclient[all]')

* group imports

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Fix likely remote URL bug

* update comment

* Update is_url()

* Fix 2x download attempt on http://path/to/model.pt

Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: glennjocher <glenn.jocher@ultralytics.com>
Co-authored-by: Gaz Iqbal <giqbal@octoml.ai>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

classify/predict.py

@@ -104,7 +104,7 @@ def run(
     seen, windows, dt = 0, [], (Profile(), Profile(), Profile())
     for path, im, im0s, vid_cap, s in dataset:
         with dt[0]:
-            im = torch.Tensor(im).to(device)
+            im = torch.Tensor(im).to(model.device)
             im = im.half() if model.fp16 else im.float()  # uint8 to fp16/32
             if len(im.shape) == 3:
                 im = im[None]  # expand for batch dim