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Fix export test matrices to exclude nms from Classify models (#18880)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Mohammed Yasin 2025-01-26 04:26:58 +08:00 • committed by GitHub
parent 83dc1fea6e
commit de05d1b655
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GPG key ID: B5690EEEBB952194
3 changed files with 46 additions and 28 deletions
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21
docs/overrides/javascript/benchmark.js
View file

@ -116,18 +116,14 @@ function updateChart(initialDatasets = []) {
EfficientDet: "#000000",
};
// Get the selected algorithms from the initialDatasets or all if empty.
const selectedAlgorithms =
initialDatasets.length > 0 ? initialDatasets : Object.keys(data);
// Create the datasets for the selected algorithms.
const datasets = selectedAlgorithms.map((algorithm, i) => {
// Always include all models in the dataset creation
const datasets = Object.keys(data).map((algorithm, i) => {
const baseColor =
colorMap[algorithm] || `hsl(${Math.random() * 360}, 70%, 50%)`;
const lineColor =
Object.keys(data).indexOf(algorithm) === 0
? baseColor
: lightenHexColor(baseColor, 0.6); // Lighten non-primary lines
: lightenHexColor(baseColor, 0.6);
return {
label: algorithm,
@ -137,14 +133,15 @@ function updateChart(initialDatasets = []) {
version: version.toUpperCase(),
})),
fill: false,
borderColor: lineColor, // Use the lightened color for the line.
borderColor: lineColor,
tension: 0.2,
pointRadius: Object.keys(data).indexOf(algorithm) === 0 ? 7 : 4,
pointHoverRadius: Object.keys(data).indexOf(algorithm) === 0 ? 9 : 6,
pointBackgroundColor: lineColor,
pointBorderColor: "#ffffff", // Add a border around points for contrast.
borderWidth: i === 0 ? 3 : 1.5, // Slightly increase line size for the primary dataset.
hidden: false,
pointBorderColor: "#ffffff",
borderWidth: i === 0 ? 3 : 1.5,
hidden:
initialDatasets.length > 0 && !initialDatasets.includes(algorithm),
};
});
@ -152,7 +149,7 @@ function updateChart(initialDatasets = []) {
modelComparisonChart = new Chart(
document.getElementById("modelComparisonChart").getContext("2d"),
{
type: "line", // Set the chart type to line.
type: "line",
data: { datasets },
options: {
//aspectRatio: 2.5, // higher is wider

38
tests/test_exports.py
View file

@ -44,18 +44,25 @@ def test_export_openvino():
@pytest.mark.skipif(not TORCH_1_13, reason="OpenVINO requires torch>=1.13")
@pytest.mark.parametrize(
"task, dynamic, int8, half, batch, nms",
[ # generate all combinations but exclude those where both int8 and half are True
[ # generate all combinations except for exclusion cases
(task, dynamic, int8, half, batch, nms)
for task, dynamic, int8, half, batch, nms in product(
TASKS, [True, False], [True, False], [True, False], [1, 2], [True, False]
)
if not (int8 and half) # exclude cases where both int8 and half are True
if not ((int8 and half) or (task == "classify" and nms))
],
)
def test_export_openvino_matrix(task, dynamic, int8, half, batch, nms):
"""Test YOLO model exports to OpenVINO under various configuration matrix conditions."""
file = YOLO(TASK2MODEL[task]).export(
format="openvino", imgsz=32, dynamic=dynamic, int8=int8, half=half, batch=batch, data=TASK2DATA[task], nms=nms
format="openvino",
imgsz=32,
dynamic=dynamic,
int8=int8,
half=half,
batch=batch,
data=TASK2DATA[task],
nms=nms,
)
if WINDOWS:
# Use unique filenames due to Windows file permissions bug possibly due to latent threaded use
@ -69,7 +76,13 @@ def test_export_openvino_matrix(task, dynamic, int8, half, batch, nms):
@pytest.mark.slow
@pytest.mark.parametrize(
"task, dynamic, int8, half, batch, simplify, nms",
product(TASKS, [True, False], [False], [False], [1, 2], [True, False], [True, False]),
[ # generate all combinations except for exclusion cases
(task, dynamic, int8, half, batch, simplify, nms)
for task, dynamic, int8, half, batch, simplify, nms in product(
TASKS, [True, False], [False], [False], [1, 2], [True, False], [True, False]
)
if not ((int8 and half) or (task == "classify" and nms))
],
)
def test_export_onnx_matrix(task, dynamic, int8, half, batch, simplify, nms):
"""Test YOLO exports to ONNX format with various configurations and parameters."""
@ -82,14 +95,19 @@ def test_export_onnx_matrix(task, dynamic, int8, half, batch, simplify, nms):
@pytest.mark.slow
@pytest.mark.parametrize(
"task, dynamic, int8, half, batch, nms", product(TASKS, [False], [False], [False], [1, 2], [True, False])
"task, dynamic, int8, half, batch, nms",
[ # generate all combinations except for exclusion cases
(task, dynamic, int8, half, batch, nms)
for task, dynamic, int8, half, batch, nms in product(TASKS, [False], [False], [False], [1, 2], [True, False])
if not (task == "classify" and nms)
],
)
def test_export_torchscript_matrix(task, dynamic, int8, half, batch, nms):
"""Tests YOLO model exports to TorchScript format under varied configurations."""
file = YOLO(TASK2MODEL[task]).export(
format="torchscript", imgsz=32, dynamic=dynamic, int8=int8, half=half, batch=batch, nms=nms
)
YOLO(file)([SOURCE] * 3, imgsz=64 if dynamic else 32) # exported model inference at batch=3
YOLO(file)([SOURCE] * batch, imgsz=64 if dynamic else 32) # exported model inference
Path(file).unlink() # cleanup
@ -99,10 +117,10 @@ def test_export_torchscript_matrix(task, dynamic, int8, half, batch, nms):
@pytest.mark.skipif(checks.IS_PYTHON_3_12, reason="CoreML not supported in Python 3.12")
@pytest.mark.parametrize(
"task, dynamic, int8, half, batch",
[ # generate all combinations but exclude those where both int8 and half are True
[ # generate all combinations except for exclusion cases
(task, dynamic, int8, half, batch)
for task, dynamic, int8, half, batch in product(TASKS, [False], [True, False], [True, False], [1])
if not (int8 and half) # exclude cases where both int8 and half are True
if not (int8 and half)
],
)
def test_export_coreml_matrix(task, dynamic, int8, half, batch):
@ -124,12 +142,12 @@ def test_export_coreml_matrix(task, dynamic, int8, half, batch):
@pytest.mark.skipif(not LINUX, reason="Test disabled as TF suffers from install conflicts on Windows and macOS")
@pytest.mark.parametrize(
"task, dynamic, int8, half, batch, nms",
[ # generate all combinations but exclude those where both int8 and half are True
[ # generate all combinations except for exclusion cases
(task, dynamic, int8, half, batch, nms)
for task, dynamic, int8, half, batch, nms in product(
TASKS, [False], [True, False], [True, False], [1], [True, False]
)
if not (int8 and half) # exclude cases where both int8 and half are True
if not ((int8 and half) or (task == "classify" and nms))
],
)
def test_export_tflite_matrix(task, dynamic, int8, half, batch, nms):

15
ultralytics/engine/exporter.py
View file

@ -75,7 +75,7 @@ from ultralytics.data.dataset import YOLODataset
from ultralytics.data.utils import check_cls_dataset, check_det_dataset
from ultralytics.nn.autobackend import check_class_names, default_class_names
from ultralytics.nn.modules import C2f, Classify, Detect, RTDETRDecoder
from ultralytics.nn.tasks import DetectionModel, SegmentationModel, WorldModel
from ultralytics.nn.tasks import ClassificationModel, DetectionModel, SegmentationModel, WorldModel
from ultralytics.utils import (
ARM64,
DEFAULT_CFG,
@ -282,6 +282,7 @@ class Exporter:
if self.args.int8 and tflite:
assert not getattr(model, "end2end", False), "TFLite INT8 export not supported for end2end models."
if self.args.nms:
assert not isinstance(model, ClassificationModel), "'nms=True' is not valid for classification models."
if getattr(model, "end2end", False):
LOGGER.warning("WARNING ⚠️ 'nms=True' is not available for end2end models. Forcing 'nms=False'.")
self.args.nms = False
@ -507,6 +508,7 @@ class Exporter:
output_names = ["output0", "output1"] if isinstance(self.model, SegmentationModel) else ["output0"]
dynamic = self.args.dynamic
if dynamic:
self.model.cpu() # dynamic=True only compatible with cpu
dynamic = {"images": {0: "batch", 2: "height", 3: "width"}} # shape(1,3,640,640)
if isinstance(self.model, SegmentationModel):
dynamic["output0"] = {0: "batch", 2: "anchors"} # shape(1, 116, 8400)
@ -518,13 +520,14 @@ class Exporter:
if self.args.nms and self.model.task == "obb":
self.args.opset = opset_version # for NMSModel
# OBB error https://github.com/pytorch/pytorch/issues/110859#issuecomment-1757841865
torch.onnx.register_custom_op_symbolic("aten::lift_fresh", lambda g, x: x, opset_version)
try:
torch.onnx.register_custom_op_symbolic("aten::lift_fresh", lambda g, x: x, opset_version)
except RuntimeError: # it will fail if it's already registered
pass
check_requirements("onnxslim>=0.1.46") # Older versions has bug with OBB
torch.onnx.export(
NMSModel(self.model.cpu() if dynamic else self.model, self.args)
if self.args.nms
else self.model, # dynamic=True only compatible with cpu
NMSModel(self.model, self.args) if self.args.nms else self.model,
self.im.cpu() if dynamic else self.im,
f,
verbose=False,
@ -1570,7 +1573,7 @@ class NMSModel(torch.nn.Module):
# TFLite GatherND error if mask is empty
score *= mask
# Explicit length otherwise reshape error, hardcoded to `self.args.max_det * 5`
mask = score.topk(self.args.max_det * 5).indices
mask = score.topk(min(self.args.max_det * 5, score.shape[0])).indices
box, score, cls, extra = box[mask], score[mask], cls[mask], extra[mask]
if not self.obb:
box = xywh2xyxy(box)