From 47151d14b14bb35fd4beaf81ed58ca087e68e40c Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Janne=20M=C3=A4yr=C3=A4?= Date: Mon, 5 Jun 2023 13:18:42 +0300 Subject: [PATCH 01/12] Change Mask to use coco-style segmentation by default --- sahi/annotation.py | 170 +++++++----------- sahi/models/detectron2.py | 8 +- sahi/models/huggingface.py | 3 +- sahi/models/mmdet.py | 7 +- sahi/models/torchvision.py | 5 +- sahi/models/yolonas.py | 3 +- sahi/models/yolov5.py | 3 +- sahi/models/yolov5sparse.py | 3 +- sahi/models/yolov8.py | 3 +- sahi/postprocess/utils.py | 21 ++- sahi/prediction.py | 21 ++- sahi/slicing.py | 2 +- sahi/utils/cv.py | 18 ++ tests/data/coco2yolo/data.yml | 4 + tests/data/coco2yolo/train/terrain2.png | 1 + tests/data/coco2yolo/train/terrain2.txt | 5 + tests/data/coco2yolo/val/terrain1.jpg | 1 + tests/data/coco2yolo/val/terrain1.txt | 7 + tests/data/export_coco_as_yolov5/data.yml | 7 + .../export_coco_as_yolov5/train/terrain1.jpg | 1 + .../export_coco_as_yolov5/train/terrain1.txt | 7 + .../export_coco_as_yolov5/train/terrain2.png | 1 + .../export_coco_as_yolov5/train/terrain2.txt | 5 + .../export_coco_as_yolov5/val/terrain1.jpg | 1 + .../export_coco_as_yolov5/val/terrain1.txt | 7 + .../export_coco_as_yolov5/val/terrain2.png | 1 + .../export_coco_as_yolov5/val/terrain2.txt | 5 + tests/test_annotation.py | 2 +- 28 files changed, 184 insertions(+), 138 deletions(-) create mode 100644 tests/data/coco2yolo/data.yml create mode 120000 tests/data/coco2yolo/train/terrain2.png create mode 100644 tests/data/coco2yolo/train/terrain2.txt create mode 120000 tests/data/coco2yolo/val/terrain1.jpg create mode 100644 tests/data/coco2yolo/val/terrain1.txt create mode 100644 tests/data/export_coco_as_yolov5/data.yml create mode 120000 tests/data/export_coco_as_yolov5/train/terrain1.jpg create mode 100644 tests/data/export_coco_as_yolov5/train/terrain1.txt create mode 120000 tests/data/export_coco_as_yolov5/train/terrain2.png create mode 100644 tests/data/export_coco_as_yolov5/train/terrain2.txt create mode 120000 tests/data/export_coco_as_yolov5/val/terrain1.jpg create mode 100644 tests/data/export_coco_as_yolov5/val/terrain1.txt create mode 120000 tests/data/export_coco_as_yolov5/val/terrain2.png create mode 100644 tests/data/export_coco_as_yolov5/val/terrain2.txt diff --git a/sahi/annotation.py b/sahi/annotation.py index 998fa0d4e..4c028843d 100644 --- a/sahi/annotation.py +++ b/sahi/annotation.py @@ -8,19 +8,12 @@ from sahi.utils.coco import CocoAnnotation, CocoPrediction from sahi.utils.cv import ( - get_bbox_from_bool_mask, + get_bbox_from_coco_segmentation, get_bool_mask_from_coco_segmentation, get_coco_segmentation_from_bool_mask, ) from sahi.utils.shapely import ShapelyAnnotation -try: - from pycocotools import mask as mask_utils - - use_rle = True -except ImportError: - use_rle = False - class BoundingBox: """ @@ -156,14 +149,13 @@ def from_float_mask( """ bool_mask = mask > mask_threshold return cls( - bool_mask=bool_mask, + segmentation=get_coco_segmentation_from_bool_mask(bool_mask), shift_amount=shift_amount, full_shape=full_shape, ) - @classmethod - def from_coco_segmentation( - cls, + def __init__( + self, segmentation, full_shape=None, shift_amount: list = [0, 0], @@ -187,39 +179,6 @@ def from_coco_segmentation( # confirm full_shape is given if full_shape is None: raise ValueError("full_shape must be provided") - bool_mask = get_bool_mask_from_coco_segmentation(segmentation, height=full_shape[0], width=full_shape[1]) - return cls( - bool_mask=bool_mask, - shift_amount=shift_amount, - full_shape=full_shape, - ) - - def __init__( - self, - bool_mask=None, - full_shape=None, - shift_amount: list = [0, 0], - ): - """ - Args: - bool_mask: np.ndarray with bool elements - 2D mask of object, should have a shape of height*width - full_shape: List - Size of the full image, should be in the form of [height, width] - shift_amount: List - To shift the box and mask predictions from sliced image to full - sized image, should be in the form of [shift_x, shift_y] - """ - - if len(bool_mask) > 0: - has_bool_mask = True - else: - has_bool_mask = False - - if has_bool_mask: - self._mask = self.encode_bool_mask(bool_mask) - else: - self._mask = None self.shift_x = shift_amount[0] self.shift_y = shift_amount[1] @@ -234,21 +193,36 @@ def __init__( self.full_shape_height = None self.full_shape_width = None - def encode_bool_mask(self, bool_mask): - _mask = bool_mask - if use_rle: - _mask = mask_utils.encode(np.asfortranarray(bool_mask.astype(np.uint8))) - return _mask + self.segmentation = segmentation - def decode_bool_mask(self, bool_mask): - _mask = bool_mask - if use_rle: - _mask = mask_utils.decode(bool_mask).astype(bool) - return _mask + @classmethod + def from_bool_mask( + cls, + bool_mask=None, + full_shape=None, + shift_amount: list = [0, 0], + ): + """ + Args: + bool_mask: np.ndarray with bool elements + 2D mask of object, should have a shape of height*width + full_shape: List + Size of the full image, should be in the form of [height, width] + shift_amount: List + To shift the box and mask predictions from sliced image to full + sized image, should be in the form of [shift_x, shift_y] + """ + return cls( + segmentation=get_coco_segmentation_from_bool_mask(bool_mask), + shift_amount=shift_amount, + full_shape=full_shape, + ) @property def bool_mask(self): - return self.decode_bool_mask(self._mask) + return get_bool_mask_from_coco_segmentation( + self.segmentation, width=self.full_shape[1], height=self.full_shape[0] + ) @property def shape(self): @@ -275,46 +249,17 @@ def get_shifted_mask(self): # Confirm full_shape is specified if (self.full_shape_height is None) or (self.full_shape_width is None): raise ValueError("full_shape is None") - # init full mask - mask_fullsized = np.full( - ( - self.full_shape_height, - self.full_shape_width, - ), - 0, - dtype="float32", - ) - - # arrange starting ending indexes - starting_pixel = [self.shift_x, self.shift_y] - ending_pixel = [ - min(starting_pixel[0] + self.bool_mask.shape[1], self.full_shape_width), - min(starting_pixel[1] + self.bool_mask.shape[0], self.full_shape_height), - ] - - # convert sliced mask to full mask - mask_fullsized[starting_pixel[1] : ending_pixel[1], starting_pixel[0] : ending_pixel[0]] = self.bool_mask[ - : ending_pixel[1] - starting_pixel[1], : ending_pixel[0] - starting_pixel[0] - ] - + shifted_segmentation = [] + for s in self.segmentation: + xs = [min(self.shift_x + s[i], self.full_shape_width) for i in range(0, len(s) - 1, 2)] + ys = [min(self.shift_y + s[i], self.full_shape_height) for i in range(1, len(s), 2)] + shifted_segmentation.append([j for i in zip(xs, ys) for j in i]) return Mask( - mask_fullsized, + segmentation=shifted_segmentation, shift_amount=[0, 0], full_shape=self.full_shape, ) - def to_coco_segmentation(self): - """ - Returns boolean mask as coco segmentation: - [ - [x1, y1, x2, y2, x3, y3, ...], - [x1, y1, x2, y2, x3, y3, ...], - ... - ] - """ - coco_segmentation = get_coco_segmentation_from_bool_mask(self.bool_mask) - return coco_segmentation - class ObjectAnnotation: """ @@ -346,9 +291,10 @@ def from_bool_mask( To shift the box and mask predictions from sliced image to full sized image, should be in the form of [shift_x, shift_y] """ + segmentation = get_coco_segmentation_from_bool_mask(bool_mask) return cls( category_id=category_id, - bool_mask=bool_mask, + segmentation=segmentation, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, @@ -388,10 +334,9 @@ def from_coco_segmentation( To shift the box and mask predictions from sliced image to full sized image, should be in the form of [shift_x, shift_y] """ - bool_mask = get_bool_mask_from_coco_segmentation(segmentation, width=full_shape[1], height=full_shape[0]) return cls( category_id=category_id, - bool_mask=bool_mask, + segmentation=segmentation, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, @@ -539,7 +484,7 @@ def from_imantics_annotation( def __init__( self, bbox: Optional[List[int]] = None, - bool_mask: Optional[np.ndarray] = None, + segmentation: Optional[np.ndarray] = None, category_id: Optional[int] = None, category_name: Optional[str] = None, shift_amount: Optional[List[int]] = [0, 0], @@ -549,8 +494,12 @@ def __init__( Args: bbox: List [minx, miny, maxx, maxy] - bool_mask: np.ndarray with bool elements - 2D mask of object, should have a shape of height*width + segmentation: List[List] + [ + [x1, y1, x2, y2, x3, y3, ...], + [x1, y1, x2, y2, x3, y3, ...], + ... + ] category_id: int ID of the object category category_name: str @@ -564,21 +513,21 @@ def __init__( """ if not isinstance(category_id, int): raise ValueError("category_id must be an integer") - if (bbox is None) and (bool_mask is None): - raise ValueError("you must provide a bbox or bool_mask") + if (bbox is None) and (segmentation is None): + raise ValueError("you must provide a bbox or segmentation") - if bool_mask is not None: + if segmentation is not None: self.mask = Mask( - bool_mask=bool_mask, + segmentation=segmentation, shift_amount=shift_amount, full_shape=full_shape, ) - bbox_from_bool_mask = get_bbox_from_bool_mask(bool_mask) + bbox_from_segmentation = get_bbox_from_coco_segmentation(segmentation) # https://github.com/obss/sahi/issues/235 - if bbox_from_bool_mask is not None: - bbox = bbox_from_bool_mask + if bbox_from_segmentation is not None: + bbox = bbox_from_segmentation else: - raise ValueError("Invalid boolean mask.") + raise ValueError("Invalid segmentation mask.") else: self.mask = None @@ -613,7 +562,7 @@ def to_coco_annotation(self): """ if self.mask: coco_annotation = CocoAnnotation.from_coco_segmentation( - segmentation=self.mask.to_coco_segmentation(), + segmentation=self.mask.segmentation(), category_id=self.category.id, category_name=self.category.name, ) @@ -631,7 +580,7 @@ def to_coco_prediction(self): """ if self.mask: coco_prediction = CocoPrediction.from_coco_segmentation( - segmentation=self.mask.to_coco_segmentation(), + segmentation=self.mask.segmentation(), category_id=self.category.id, category_name=self.category.name, score=1, @@ -651,7 +600,7 @@ def to_shapely_annotation(self): """ if self.mask: shapely_annotation = ShapelyAnnotation.from_coco_segmentation( - segmentation=self.mask.to_coco_segmentation(), + segmentation=self.mask.segmentation(), ) else: shapely_annotation = ShapelyAnnotation.from_coco_bbox( @@ -695,13 +644,14 @@ def get_empty_mask(cls): def get_shifted_object_annotation(self): if self.mask: + shifted_mask = self.mask.get_shifted_mask() return ObjectAnnotation( bbox=self.bbox.get_shifted_box().to_xyxy(), category_id=self.category.id, - bool_mask=self.mask.get_shifted_mask().bool_mask, + segmentation=shifted_mask.segmentation, category_name=self.category.name, shift_amount=[0, 0], - full_shape=self.mask.get_shifted_mask().full_shape, + full_shape=shifted_mask.full_shape, ) else: return ObjectAnnotation( diff --git a/sahi/models/detectron2.py b/sahi/models/detectron2.py index 5f67507ca..8fe8dd7e2 100644 --- a/sahi/models/detectron2.py +++ b/sahi/models/detectron2.py @@ -8,7 +8,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction -from sahi.utils.cv import get_bbox_from_bool_mask +from sahi.utils.cv import get_bbox_from_bool_mask, get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements logger = logging.getLogger(__name__) @@ -150,7 +150,9 @@ def _create_object_prediction_list_from_original_predictions( object_prediction_list = [ ObjectPrediction( bbox=box.tolist() if mask is None else None, - bool_mask=mask.detach().cpu().numpy() if mask is not None else None, + segmentation=get_coco_segmentation_from_bool_mask(mask.detach().cpu().numpy()) + if mask is not None + else None, category_id=category_id.item(), category_name=self.category_mapping[str(category_id.item())], shift_amount=shift_amount, @@ -164,7 +166,7 @@ def _create_object_prediction_list_from_original_predictions( object_prediction_list = [ ObjectPrediction( bbox=box.tolist(), - bool_mask=None, + segmentation=None, category_id=category_id.item(), category_name=self.category_mapping[str(category_id.item())], shift_amount=shift_amount, diff --git a/sahi/models/huggingface.py b/sahi/models/huggingface.py index ad21e19b7..2549a29b8 100644 --- a/sahi/models/huggingface.py +++ b/sahi/models/huggingface.py @@ -10,6 +10,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements, ensure_package_minimum_version logger = logging.getLogger(__name__) @@ -198,7 +199,7 @@ def _create_object_prediction_list_from_original_predictions( object_prediction = ObjectPrediction( bbox=bbox, - bool_mask=None, + segmentation=None, category_id=category_id, category_name=self.category_mapping[category_id], shift_amount=shift_amount, diff --git a/sahi/models/mmdet.py b/sahi/models/mmdet.py index 49820dd29..999dd6015 100644 --- a/sahi/models/mmdet.py +++ b/sahi/models/mmdet.py @@ -9,7 +9,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list -from sahi.utils.cv import get_bbox_from_bool_mask +from sahi.utils.cv import get_bbox_from_bool_mask, get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements logger = logging.getLogger(__name__) @@ -167,8 +167,9 @@ def _create_object_prediction_list_from_original_predictions( # https://github.com/obss/sahi/discussions/696 if get_bbox_from_bool_mask(bool_mask) is None: continue + segmentation = get_coco_segmentation_from_bool_mask else: - bool_mask = None + segmentation = None # fix negative box coords bbox[0] = max(0, bbox[0]) @@ -192,7 +193,7 @@ def _create_object_prediction_list_from_original_predictions( bbox=bbox, category_id=category_id, score=score, - bool_mask=bool_mask, + segmentation=segmentation, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, diff --git a/sahi/models/torchvision.py b/sahi/models/torchvision.py index 3685300e5..c7fb683b4 100644 --- a/sahi/models/torchvision.py +++ b/sahi/models/torchvision.py @@ -8,6 +8,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements logger = logging.getLogger(__name__) @@ -176,13 +177,13 @@ def _create_object_prediction_list_from_original_predictions( for ind in range(len(boxes)): if masks is not None: - mask = np.array(masks[ind]) + mask = get_coco_segmentation_from_bool_mask(np.array(masks[ind])) else: mask = None object_prediction = ObjectPrediction( bbox=boxes[ind], - bool_mask=mask, + segmentation=mask, category_id=int(category_ids[ind]), category_name=self.category_mapping[str(int(category_ids[ind]))], shift_amount=shift_amount, diff --git a/sahi/models/yolonas.py b/sahi/models/yolonas.py index e33c11592..05568a614 100644 --- a/sahi/models/yolonas.py +++ b/sahi/models/yolonas.py @@ -10,6 +10,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements logger = logging.getLogger(__name__) @@ -182,7 +183,7 @@ def _create_object_prediction_list_from_original_predictions( bbox=bbox, category_id=int(category_id), score=score, - bool_mask=None, + segmentation=None, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, diff --git a/sahi/models/yolov5.py b/sahi/models/yolov5.py index e864b008b..2fc5aa3d5 100644 --- a/sahi/models/yolov5.py +++ b/sahi/models/yolov5.py @@ -9,6 +9,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_package_minimum_version, check_requirements logger = logging.getLogger(__name__) @@ -157,7 +158,7 @@ def _create_object_prediction_list_from_original_predictions( bbox=bbox, category_id=category_id, score=score, - bool_mask=None, + segmentation=None, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, diff --git a/sahi/models/yolov5sparse.py b/sahi/models/yolov5sparse.py index 4c22910cb..61f5a0e81 100644 --- a/sahi/models/yolov5sparse.py +++ b/sahi/models/yolov5sparse.py @@ -11,6 +11,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_package_minimum_version, check_requirements logger = logging.getLogger(__name__) @@ -209,7 +210,7 @@ def _create_object_prediction_list_from_original_predictions( bbox=bbox, category_id=category_id, score=score, - bool_mask=None, + segmentation=None, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, diff --git a/sahi/models/yolov8.py b/sahi/models/yolov8.py index f8ba492be..83718067f 100644 --- a/sahi/models/yolov8.py +++ b/sahi/models/yolov8.py @@ -11,6 +11,7 @@ from sahi.models.base import DetectionModel from sahi.prediction import ObjectPrediction from sahi.utils.compatibility import fix_full_shape_list, fix_shift_amount_list +from sahi.utils.cv import get_coco_segmentation_from_bool_mask from sahi.utils.import_utils import check_requirements @@ -145,7 +146,7 @@ def _create_object_prediction_list_from_original_predictions( bbox=bbox, category_id=category_id, score=score, - bool_mask=None, + segmentation=None, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, diff --git a/sahi/postprocess/utils.py b/sahi/postprocess/utils.py index 80f7bd43e..6008e0be1 100644 --- a/sahi/postprocess/utils.py +++ b/sahi/postprocess/utils.py @@ -3,9 +3,12 @@ import numpy as np import torch +from shapely.geometry import MultiPolygon, Polygon from sahi.annotation import BoundingBox, Category, Mask from sahi.prediction import ObjectPrediction +from sahi.utils.cv import get_coco_segmentation_from_bool_mask +from sahi.utils.shapely import ShapelyAnnotation, get_shapely_multipolygon class ObjectPredictionList(Sequence): @@ -160,9 +163,17 @@ def has_match( def get_merged_mask(pred1: ObjectPrediction, pred2: ObjectPrediction) -> Mask: mask1 = pred1.mask mask2 = pred2.mask - union_mask = np.logical_or(mask1.bool_mask, mask2.bool_mask) + + poly1 = get_shapely_multipolygon(mask1.segmentation).buffer(0) + poly2 = get_shapely_multipolygon(mask2.segmentation).buffer(0) + union_poly = poly1.union(poly2) + if not hasattr(union_poly, "geoms"): + union_poly = MultiPolygon([union_poly]) + else: + union_poly = MultiPolygon([g.buffer(0) for g in union_poly.geoms if isinstance(g, Polygon)]) + union = ShapelyAnnotation(multipolygon=union_poly).to_coco_segmentation() return Mask( - bool_mask=union_mask, + segmentation=union, full_shape=mask1.full_shape, shift_amount=mask1.shift_amount, ) @@ -200,17 +211,17 @@ def merge_object_prediction_pair( merged_category: Category = get_merged_category(pred1, pred2) if pred1.mask and pred2.mask: merged_mask: Mask = get_merged_mask(pred1, pred2) - bool_mask = merged_mask.bool_mask + segmentation = merged_mask.segmentation full_shape = merged_mask.full_shape else: - bool_mask = None + segmentation = None full_shape = None return ObjectPrediction( bbox=merged_bbox.to_xyxy(), score=merged_score, category_id=merged_category.id, category_name=merged_category.name, - bool_mask=bool_mask, + segmentation=segmentation, shift_amount=shift_amount, full_shape=full_shape, ) diff --git a/sahi/prediction.py b/sahi/prediction.py index 7475d15f7..56599d8c1 100644 --- a/sahi/prediction.py +++ b/sahi/prediction.py @@ -45,13 +45,13 @@ def __init__( bbox: Optional[List[int]] = None, category_id: Optional[int] = None, category_name: Optional[str] = None, - bool_mask: Optional[np.ndarray] = None, + segmentation: Optional[np.ndarray] = None, score: Optional[float] = 0, shift_amount: Optional[List[int]] = [0, 0], full_shape: Optional[List[int]] = None, ): """ - Creates ObjectPrediction from bbox, score, category_id, category_name, bool_mask. + Creates ObjectPrediction from bbox, score, category_id, category_name, segmentation. Arguments: bbox: list @@ -62,8 +62,12 @@ def __init__( ID of the object category category_name: str Name of the object category - bool_mask: np.ndarray - 2D boolean mask array. Should be None if model doesn't output segmentation mask. + segmentation: List[List] + [ + [x1, y1, x2, y2, x3, y3, ...], + [x1, y1, x2, y2, x3, y3, ...], + ... + ] shift_amount: list To shift the box and mask predictions from sliced image to full sized image, should be in the form of [shift_x, shift_y] @@ -75,7 +79,7 @@ def __init__( super().__init__( bbox=bbox, category_id=category_id, - bool_mask=bool_mask, + segmentation=segmentation, category_name=category_name, shift_amount=shift_amount, full_shape=full_shape, @@ -88,21 +92,22 @@ def get_shifted_object_prediction(self): Used for mapping sliced predictions over full image. """ if self.mask: + shifted_mask = self.mask.get_shifted_mask() return ObjectPrediction( bbox=self.bbox.get_shifted_box().to_xyxy(), category_id=self.category.id, score=self.score.value, - bool_mask=self.mask.get_shifted_mask().bool_mask, + segmentation=shifted_mask.segmentation, category_name=self.category.name, shift_amount=[0, 0], - full_shape=self.mask.get_shifted_mask().full_shape, + full_shape=shifted_mask.full_shape, ) else: return ObjectPrediction( bbox=self.bbox.get_shifted_box().to_xyxy(), category_id=self.category.id, score=self.score.value, - bool_mask=None, + segmentation=None, category_name=self.category.name, shift_amount=[0, 0], full_shape=None, diff --git a/sahi/slicing.py b/sahi/slicing.py index 163bcfb44..4633f7535 100644 --- a/sahi/slicing.py +++ b/sahi/slicing.py @@ -695,7 +695,7 @@ def shift_masks(masks: np.ndarray, offset: Sequence[int], full_shape: Sequence[i shifted_masks = [] for mask in masks: - mask = Mask(bool_mask=mask, shift_amount=offset, full_shape=full_shape) + mask = Mask(segmentation=mask, shift_amount=offset, full_shape=full_shape) mask = mask.get_shifted_mask() shifted_masks.append(mask.bool_mask) diff --git a/sahi/utils/cv.py b/sahi/utils/cv.py index 0204df498..5e802eb7f 100644 --- a/sahi/utils/cv.py +++ b/sahi/utils/cv.py @@ -573,6 +573,24 @@ def get_bbox_from_bool_mask(bool_mask): return [xmin, ymin, xmax, ymax] +def get_bbox_from_coco_segmentation(coco_segmentation): + """ + Generate voc box ([xmin, ymin, xmax, ymax]) from given coco segmentation + """ + xs = [] + ys = [] + for segm in coco_segmentation: + xs.extend(segm[::2]) + ys.extend(segm[1::2]) + if len(xs) == 0 or len(ys) == 0: + return None + xmin = min(xs) + xmax = max(xs) + ymin = min(ys) + ymax = max(ys) + return [xmin, ymin, xmax, ymax] + + def normalize_numpy_image(image: np.ndarray): """ Normalizes numpy image diff --git a/tests/data/coco2yolo/data.yml b/tests/data/coco2yolo/data.yml new file mode 100644 index 000000000..b02e83724 --- /dev/null +++ b/tests/data/coco2yolo/data.yml @@ -0,0 +1,4 @@ +names: [human, car, big_vehicle] +nc: 3 +train: /mnt/d/Users/E1005164/sahi/tests/data/coco2yolo/train +val: /mnt/d/Users/E1005164/sahi/tests/data/coco2yolo/val diff --git a/tests/data/coco2yolo/train/terrain2.png b/tests/data/coco2yolo/train/terrain2.png new file mode 120000 index 000000000..b616b85ff --- /dev/null +++ b/tests/data/coco2yolo/train/terrain2.png @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain2.png \ No newline at end of file diff --git a/tests/data/coco2yolo/train/terrain2.txt b/tests/data/coco2yolo/train/terrain2.txt new file mode 100644 index 000000000..c5577a2af --- /dev/null +++ b/tests/data/coco2yolo/train/terrain2.txt @@ -0,0 +1,5 @@ +2 0.3212890625 0.7749266862170088 0.216796875 0.23607038123167157 +2 0.54833984375 0.7287390029325513 0.1181640625 0.1348973607038123 +2 0.65869140625 0.6818181818181818 0.0791015625 0.08211143695014662 +2 0.7421875 0.657624633431085 0.068359375 0.0747800586510264 +2 0.7919921875 0.6268328445747801 0.0390625 0.0689149560117302 diff --git a/tests/data/coco2yolo/val/terrain1.jpg b/tests/data/coco2yolo/val/terrain1.jpg new file mode 120000 index 000000000..5be5e33c9 --- /dev/null +++ b/tests/data/coco2yolo/val/terrain1.jpg @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain1.jpg \ No newline at end of file diff --git a/tests/data/coco2yolo/val/terrain1.txt b/tests/data/coco2yolo/val/terrain1.txt new file mode 100644 index 000000000..1bb5dac7b --- /dev/null +++ b/tests/data/coco2yolo/val/terrain1.txt @@ -0,0 +1,7 @@ +1 0.277099609375 0.8249084249084249 0.07470703125 0.13333333333333333 +1 0.334228515625 0.836996336996337 0.03564453125 0.12527472527472527 +1 0.432861328125 0.8300366300366301 0.03369140625 0.11721611721611722 +1 0.453369140625 0.8168498168498168 0.02783203125 0.12161172161172161 +1 0.47119140625 0.8168498168498168 0.0234375 0.11135531135531135 +1 0.5966796875 0.815018315018315 0.03125 0.0945054945054945 +1 0.669189453125 0.8179487179487179 0.04638671875 0.10036630036630037 diff --git a/tests/data/export_coco_as_yolov5/data.yml b/tests/data/export_coco_as_yolov5/data.yml new file mode 100644 index 000000000..6fc4fe68b --- /dev/null +++ b/tests/data/export_coco_as_yolov5/data.yml @@ -0,0 +1,7 @@ +names: +- human +- car +- big_vehicle +nc: 3 +train: /mnt/d/Users/E1005164/sahi/tests/data/export_coco_as_yolov5/train +val: /mnt/d/Users/E1005164/sahi/tests/data/export_coco_as_yolov5/val diff --git a/tests/data/export_coco_as_yolov5/train/terrain1.jpg b/tests/data/export_coco_as_yolov5/train/terrain1.jpg new file mode 120000 index 000000000..5be5e33c9 --- /dev/null +++ b/tests/data/export_coco_as_yolov5/train/terrain1.jpg @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain1.jpg \ No newline at end of file diff --git a/tests/data/export_coco_as_yolov5/train/terrain1.txt b/tests/data/export_coco_as_yolov5/train/terrain1.txt new file mode 100644 index 000000000..1bb5dac7b --- /dev/null +++ b/tests/data/export_coco_as_yolov5/train/terrain1.txt @@ -0,0 +1,7 @@ +1 0.277099609375 0.8249084249084249 0.07470703125 0.13333333333333333 +1 0.334228515625 0.836996336996337 0.03564453125 0.12527472527472527 +1 0.432861328125 0.8300366300366301 0.03369140625 0.11721611721611722 +1 0.453369140625 0.8168498168498168 0.02783203125 0.12161172161172161 +1 0.47119140625 0.8168498168498168 0.0234375 0.11135531135531135 +1 0.5966796875 0.815018315018315 0.03125 0.0945054945054945 +1 0.669189453125 0.8179487179487179 0.04638671875 0.10036630036630037 diff --git a/tests/data/export_coco_as_yolov5/train/terrain2.png b/tests/data/export_coco_as_yolov5/train/terrain2.png new file mode 120000 index 000000000..b616b85ff --- /dev/null +++ b/tests/data/export_coco_as_yolov5/train/terrain2.png @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain2.png \ No newline at end of file diff --git a/tests/data/export_coco_as_yolov5/train/terrain2.txt b/tests/data/export_coco_as_yolov5/train/terrain2.txt new file mode 100644 index 000000000..c5577a2af --- /dev/null +++ b/tests/data/export_coco_as_yolov5/train/terrain2.txt @@ -0,0 +1,5 @@ +2 0.3212890625 0.7749266862170088 0.216796875 0.23607038123167157 +2 0.54833984375 0.7287390029325513 0.1181640625 0.1348973607038123 +2 0.65869140625 0.6818181818181818 0.0791015625 0.08211143695014662 +2 0.7421875 0.657624633431085 0.068359375 0.0747800586510264 +2 0.7919921875 0.6268328445747801 0.0390625 0.0689149560117302 diff --git a/tests/data/export_coco_as_yolov5/val/terrain1.jpg b/tests/data/export_coco_as_yolov5/val/terrain1.jpg new file mode 120000 index 000000000..5be5e33c9 --- /dev/null +++ b/tests/data/export_coco_as_yolov5/val/terrain1.jpg @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain1.jpg \ No newline at end of file diff --git a/tests/data/export_coco_as_yolov5/val/terrain1.txt b/tests/data/export_coco_as_yolov5/val/terrain1.txt new file mode 100644 index 000000000..1bb5dac7b --- /dev/null +++ b/tests/data/export_coco_as_yolov5/val/terrain1.txt @@ -0,0 +1,7 @@ +1 0.277099609375 0.8249084249084249 0.07470703125 0.13333333333333333 +1 0.334228515625 0.836996336996337 0.03564453125 0.12527472527472527 +1 0.432861328125 0.8300366300366301 0.03369140625 0.11721611721611722 +1 0.453369140625 0.8168498168498168 0.02783203125 0.12161172161172161 +1 0.47119140625 0.8168498168498168 0.0234375 0.11135531135531135 +1 0.5966796875 0.815018315018315 0.03125 0.0945054945054945 +1 0.669189453125 0.8179487179487179 0.04638671875 0.10036630036630037 diff --git a/tests/data/export_coco_as_yolov5/val/terrain2.png b/tests/data/export_coco_as_yolov5/val/terrain2.png new file mode 120000 index 000000000..b616b85ff --- /dev/null +++ b/tests/data/export_coco_as_yolov5/val/terrain2.png @@ -0,0 +1 @@ +/mnt/d/Users/E1005164/sahi/tests/data/coco_utils/terrain2.png \ No newline at end of file diff --git a/tests/data/export_coco_as_yolov5/val/terrain2.txt b/tests/data/export_coco_as_yolov5/val/terrain2.txt new file mode 100644 index 000000000..c5577a2af --- /dev/null +++ b/tests/data/export_coco_as_yolov5/val/terrain2.txt @@ -0,0 +1,5 @@ +2 0.3212890625 0.7749266862170088 0.216796875 0.23607038123167157 +2 0.54833984375 0.7287390029325513 0.1181640625 0.1348973607038123 +2 0.65869140625 0.6818181818181818 0.0791015625 0.08211143695014662 +2 0.7421875 0.657624633431085 0.068359375 0.0747800586510264 +2 0.7919921875 0.6268328445747801 0.0390625 0.0689149560117302 diff --git a/tests/test_annotation.py b/tests/test_annotation.py index 6f2901052..1c68a5776 100644 --- a/tests/test_annotation.py +++ b/tests/test_annotation.py @@ -38,7 +38,7 @@ def test_mask(self): full_shape_height, full_shape_width = 500, 600 full_shape = [full_shape_height, full_shape_width] - mask = Mask.from_coco_segmentation(segmentation=coco_segmentation, full_shape=full_shape) + mask = Mask(segmentation=coco_segmentation, full_shape=full_shape) self.assertEqual(mask.full_shape_height, full_shape_height) self.assertEqual(mask.full_shape_width, full_shape_width) From 850f2e05e25c7eb09ac1225652d6d8a64df1bff5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Janne=20M=C3=A4yr=C3=A4?= Date: Mon, 5 Jun 2023 14:00:17 +0300 Subject: [PATCH 02/12] remove `has_bool_mask` from annotation --- sahi/annotation.py | 3 --- 1 file changed, 3 deletions(-) diff --git a/sahi/annotation.py b/sahi/annotation.py index 4c028843d..472e4b922 100644 --- a/sahi/annotation.py +++ b/sahi/annotation.py @@ -186,9 +186,6 @@ def __init__( if full_shape: self.full_shape_height = full_shape[0] self.full_shape_width = full_shape[1] - elif has_bool_mask: - self.full_shape_height = self.bool_mask.shape[0] - self.full_shape_width = self.bool_mask.shape[1] else: self.full_shape_height = None self.full_shape_width = None From 8cc2c154c207b0c22716987cfd88233b53f57bd5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Janne=20M=C3=A4yr=C3=A4?= Date: Mon, 5 Jun 2023 14:23:37 +0300 Subject: [PATCH 03/12] fix tests --- tests/test_detectron2.py | 5 ++--- tests/test_highlevelapi.py | 2 +- tests/test_mmdetectionmodel.py | 2 +- 3 files changed, 4 insertions(+), 5 deletions(-) diff --git a/tests/test_detectron2.py b/tests/test_detectron2.py index abaf26ea3..de667dc6e 100644 --- a/tests/test_detectron2.py +++ b/tests/test_detectron2.py @@ -15,7 +15,7 @@ # note that detectron2 binaries are available only for linux torch_version = get_package_info("torch", verbose=False)[1] -if "1.10." in torch_version: +if "1.10." in torch_version or "2." in torch_version: class TestDetectron2DetectionModel(unittest.TestCase): def test_load_model(self): @@ -117,12 +117,11 @@ def test_convert_original_predictions_with_mask_output(self): # prepare image image_path = "tests/data/small-vehicles1.jpeg" image = read_image(image_path) - # perform inference detectron2_detection_model.perform_inference(image) # convert predictions to ObjectPrediction list - detectron2_detection_model.convert_original_predictions() + detectron2_detection_model.convert_original_predictions(full_shape=(image.shape[0], image.shape[1])) object_prediction_list = detectron2_detection_model.object_prediction_list # compare diff --git a/tests/test_highlevelapi.py b/tests/test_highlevelapi.py index fe8adee5e..2247b568f 100644 --- a/tests/test_highlevelapi.py +++ b/tests/test_highlevelapi.py @@ -38,7 +38,7 @@ def test_mask(self): full_shape_height, full_shape_width = 500, 600 full_shape = [full_shape_height, full_shape_width] - mask = Mask.from_coco_segmentation(segmentation=coco_segmentation, full_shape=full_shape) + mask = Mask(segmentation=coco_segmentation, full_shape=full_shape) self.assertEqual(mask.full_shape_height, full_shape_height) self.assertEqual(mask.full_shape_width, full_shape_width) diff --git a/tests/test_mmdetectionmodel.py b/tests/test_mmdetectionmodel.py index f78848cee..85df08add 100644 --- a/tests/test_mmdetectionmodel.py +++ b/tests/test_mmdetectionmodel.py @@ -143,7 +143,7 @@ def test_convert_original_predictions_with_mask_output(self): mmdet_detection_model.perform_inference(image) # convert predictions to ObjectPrediction list - mmdet_detection_model.convert_original_predictions() + mmdet_detection_model.convert_original_predictions(full_shape=(image.shape[0], image.shape[1])) object_predictions = mmdet_detection_model.object_prediction_list # compare From 632687f489b91fc70af50d0f882c6544ff8a5c04 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Janne=20M=C3=A4yr=C3=A4?= Date: Mon, 5 Jun 2023 14:37:46 +0300 Subject: [PATCH 04/12] fix mmdet --- sahi/models/mmdet.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/sahi/models/mmdet.py b/sahi/models/mmdet.py index 999dd6015..633c3c8b8 100644 --- a/sahi/models/mmdet.py +++ b/sahi/models/mmdet.py @@ -167,7 +167,7 @@ def _create_object_prediction_list_from_original_predictions( # https://github.com/obss/sahi/discussions/696 if get_bbox_from_bool_mask(bool_mask) is None: continue - segmentation = get_coco_segmentation_from_bool_mask + segmentation = get_coco_segmentation_from_bool_mask(bool_mask) else: segmentation = None From a60eb034ad4aa54690313d9b0875ff5bdae43721 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Janne=20M=C3=A4yr=C3=A4?= Date: Mon, 5 Jun 2023 13:18:42 +0300 Subject: [PATCH 05/12] Change Mask to use coco-style segmentation by default --- demo/demo_data/prediction_visual.png | Bin 0 -> 1116368 bytes demo/inference_for_mmdetection.ipynb | 204 +++++--- demo/inference_for_yolov8.ipynb | 418 +++++++++++---- .../cascade-mask-rcnn_r50_fpn_1x_coco.py | 461 +++++++++++++++++ sahi/annotation.py | 168 +++--- sahi/models/detectron2.py | 9 +- sahi/models/huggingface.py | 3 +- sahi/models/mmdet.py | 10 +- sahi/models/torchvision.py | 5 +- sahi/models/yolonas.py | 3 +- sahi/models/yolov5.py | 3 +- sahi/models/yolov5sparse.py | 3 +- sahi/models/yolov8.py | 162 ++++-- sahi/models/yolov8onnx.py | 2 +- sahi/postprocess/utils.py | 21 +- sahi/predict.py | 7 +- sahi/prediction.py | 23 +- sahi/slicing.py | 2 +- sahi/utils/cv.py | 19 +- sahi/utils/yolov8.py | 83 +++ tests/data/coco2yolo/data.yml | 4 + tests/data/coco2yolo/train/terrain2.png | 1 + tests/data/coco2yolo/train/terrain2.txt | 5 + tests/data/coco2yolo/val/terrain1.jpg | 1 + tests/data/coco2yolo/val/terrain1.txt | 7 + tests/data/export_coco_as_yolov5/data.yml | 7 + .../export_coco_as_yolov5/train/terrain1.jpg | 1 + .../export_coco_as_yolov5/train/terrain1.txt | 7 + .../export_coco_as_yolov5/train/terrain2.png | 1 + .../export_coco_as_yolov5/train/terrain2.txt | 5 + .../export_coco_as_yolov5/val/terrain1.jpg | 1 + .../export_coco_as_yolov5/val/terrain1.txt | 7 + .../export_coco_as_yolov5/val/terrain2.png | 1 + .../export_coco_as_yolov5/val/terrain2.txt | 5 + tests/test_annotation.py | 2 +- tests/test_detectron2.py | 481 +++++++++--------- tests/test_mmdetectionmodel.py | 4 +- tests/test_yolov8model.py | 93 +++- 38 files changed, 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