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[ONNX] Scripting nms on boxes to dynamically export detection/no detection #2052

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[ONNX] Scripting nms on boxes to dynamically export detection/no detection #2052

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8982ff6
Fixing nms on boxes when no detection
neginraoof Apr 2, 2020
21f94fd
test
neginraoof Apr 8, 2020
c7779ad
Merge branch 'master' of https://github.com/pytorch/vision into nerao…
neginraoof Apr 8, 2020
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3 changes: 2 additions & 1 deletion torchvision/__init__.py
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Original file line number Diff line number Diff line change
@@ -1,13 +1,14 @@
import warnings

from .extension import _HAS_OPS

from torchvision import models
from torchvision import datasets
from torchvision import ops
from torchvision import transforms
from torchvision import utils
from torchvision import io

from .extension import _HAS_OPS
import torch

try:
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2 changes: 1 addition & 1 deletion torchvision/models/detection/transform.py
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Expand Up @@ -223,4 +223,4 @@ def resize_boxes(boxes, original_size, new_size):
xmax = xmax * ratio_width
ymin = ymin * ratio_height
ymax = ymax * ratio_height
return torch.stack((xmin, ymin, xmax, ymax), dim=1)
return torch.stack((xmin, ymin, xmax, ymax), dim=1)
2 changes: 2 additions & 0 deletions torchvision/ops/boxes.py
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Expand Up @@ -4,6 +4,7 @@
import torchvision


@torch.jit.script
def nms(boxes, scores, iou_threshold):
# type: (Tensor, Tensor, float)
"""
Expand Down Expand Up @@ -35,6 +36,7 @@ def nms(boxes, scores, iou_threshold):
return torch.ops.torchvision.nms(boxes, scores, iou_threshold)


@torch.jit.script
def batched_nms(boxes, scores, idxs, iou_threshold):
# type: (Tensor, Tensor, Tensor, float)
"""
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