feat(mge/data): add objects365 dataset

GitOrigin-RevId: 8eccebfc1de6a03b549f3dae1783fe17015cd723

python_module/megengine/data/dataset/vision/__init__.py

@@ -13,4 +13,5 @@ from .folder import ImageFolder
 from .imagenet import ImageNet
 from .meta_vision import VisionDataset
 from .mnist import MNIST
+from .objects365 import Objects365
 from .voc import PascalVOC

python_module/megengine/data/dataset/vision/objects365.py

+# -*- coding: utf-8 -*-
+# MegEngine is Licensed under the Apache License, Version 2.0 (the "License")
+#
+# Copyright (c) 2014-2020 Megvii Inc. All rights reserved.
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT ARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# ---------------------------------------------------------------------
+# Part of the following code in this file refs to maskrcnn-benchmark
+# MIT License
+#
+# Copyright (c) 2018 Facebook
+# ---------------------------------------------------------------------
+import json
+import os
+from collections import defaultdict
+
+import cv2
+import numpy as np
+
+from .meta_vision import VisionDataset
+
+
+class Objects365(VisionDataset):
+    r"""`Objects365 <https://www.objects365.org/overview.html>`_ Dataset.
+    """
+
+    supported_order = (
+        "image",
+        "boxes",
+        "boxes_category",
+        "info",
+    )
+
+    def __init__(
+        self, root, ann_file, remove_images_without_annotations=False, *, order=None
+    ):
+        super().__init__(root, order=order, supported_order=self.supported_order)
+
+        with open(ann_file, "r") as f:
+            dataset = json.load(f)
+
+        self.imgs = dict()
+        for img in dataset["images"]:
+            self.imgs[img["id"]] = img
+
+        self.img_to_anns = defaultdict(list)
+        for ann in dataset["annotations"]:
+            # for saving memory
+            if (
+                "boxes" not in self.order
+                and "boxes_category" not in self.order
+                and "bbox" in ann
+            ):
+                del ann["bbox"]
+            self.img_to_anns[ann["image_id"]].append(ann)
+
+        self.cats = dict()
+        for cat in dataset["categories"]:
+            self.cats[cat["id"]] = cat
+
+        self.ids = list(sorted(self.imgs.keys()))
+
+        # filter images without detection annotations
+        if remove_images_without_annotations:
+            ids = []
+            for img_id in self.ids:
+                anno = self.img_to_anns[img_id]
+                # filter crowd annotations
+                anno = [obj for obj in anno if obj["iscrowd"] == 0]
+                anno = [obj for obj in anno if obj["bbox"][2] > 0 and obj["bbox"][3] > 0]
+                if len(anno) > 0:
+                    ids.append(img_id)
+                    self.img_to_anns[img_id] = anno
+                else:
+                    del self.imgs[img_id]
+                    del self.img_to_anns[img_id]
+            self.ids = ids
+
+        self.json_category_id_to_contiguous_id = {
+            v: i + 1 for i, v in enumerate(self.cats.keys())
+        }
+
+        self.contiguous_category_id_to_json_id = {
+            v: k for k, v in self.json_category_id_to_contiguous_id.items()
+        }
+
+    def __getitem__(self, index):
+        img_id = self.ids[index]
+        anno = self.img_to_anns[img_id]
+
+        target = []
+        for k in self.order:
+            if k == "image":
+                file_name = self.imgs[img_id]["file_name"]
+                path = os.path.join(self.root, file_name)
+                image = cv2.imread(path, cv2.IMREAD_COLOR)
+                target.append(image)
+            elif k == "boxes":
+                boxes = [obj["bbox"] for obj in anno]
+                boxes = np.array(boxes, dtype=np.float32).reshape(-1, 4)
+                # transfer boxes from xywh to xyxy
+                boxes[:, 2:] += boxes[:, :2]
+                target.append(boxes)
+            elif k == "boxes_category":
+                boxes_category = [obj["category_id"] for obj in anno]
+                boxes_category = [
+                    self.json_category_id_to_contiguous_id[c] for c in boxes_category
+                ]
+                boxes_category = np.array(boxes_category, dtype=np.int32)
+                target.append(boxes_category)
+            elif k == "info":
+                info = self.imgs[img_id]
+                info = [info["height"], info["width"], info["file_name"]]
+                target.append(info)
+            else:
+                raise NotImplementedError
+
+        return tuple(target)
+
+    def __len__(self):
+        return len(self.ids)
+
+    def get_img_info(self, index):
+        img_id = self.ids[index]
+        img_info = self.imgs[img_id]
+        return img_info
+
+    class_name = (
+        "person",
+        "sneakers",
+        "chair",
+        "hat",
+        "lamp",
+        "bottle",
+        "cabinet/shelf",
+        "cup",
+        "car",
+        "glasses",
+        "picture/frame",
+        "desk",
+        "handbag",
+        "street lights",
+        "book",
+        "plate",
+        "helmet",
+        "leather shoes",
+        "pillow",
+        "glove",
+        "potted plant",
+        "bracelet",
+        "flower",
+        "tv",
+        "storage box",
+        "vase",
+        "bench",
+        "wine glass",
+        "boots",
+        "bowl",
+        "dining table",
+        "umbrella",
+        "boat",
+        "flag",
+        "speaker",
+        "trash bin/can",
+        "stool",
+        "backpack",
+        "couch",
+        "belt",
+        "carpet",
+        "basket",
+        "towel/napkin",
+        "slippers",
+        "barrel/bucket",
+        "coffee table",
+        "suv",
+        "toy",
+        "tie",
+        "bed",
+        "traffic light",
+        "pen/pencil",
+        "microphone",
+        "sandals",
+        "canned",
+        "necklace",
+        "mirror",
+        "faucet",
+        "bicycle",
+        "bread",
+        "high heels",
+        "ring",
+        "van",
+        "watch",
+        "sink",
+        "horse",
+        "fish",
+        "apple",
+        "camera",
+        "candle",
+        "teddy bear",
+        "cake",
+        "motorcycle",
+        "wild bird",
+        "laptop",
+        "knife",
+        "traffic sign",
+        "cell phone",
+        "paddle",
+        "truck",
+        "cow",
+        "power outlet",
+        "clock",
+        "drum",
+        "fork",
+        "bus",
+        "hanger",
+        "nightstand",
+        "pot/pan",
+        "sheep",
+        "guitar",
+        "traffic cone",
+        "tea pot",
+        "keyboard",
+        "tripod",
+        "hockey",
+        "fan",
+        "dog",
+        "spoon",
+        "blackboard/whiteboard",
+        "balloon",
+        "air conditioner",
+        "cymbal",
+        "mouse",
+        "telephone",
+        "pickup truck",
+        "orange",
+        "banana",
+        "airplane",
+        "luggage",
+        "skis",
+        "soccer",
+        "trolley",
+        "oven",
+        "remote",
+        "baseball glove",
+        "paper towel",
+        "refrigerator",
+        "train",
+        "tomato",
+        "machinery vehicle",
+        "tent",
+        "shampoo/shower gel",
+        "head phone",
+        "lantern",
+        "donut",
+        "cleaning products",
+        "sailboat",
+        "tangerine",
+        "pizza",
+        "kite",
+        "computer box",
+        "elephant",
+        "toiletries",
+        "gas stove",
+        "broccoli",
+        "toilet",
+        "stroller",
+        "shovel",
+        "baseball bat",
+        "microwave",
+        "skateboard",
+        "surfboard",
+        "surveillance camera",
+        "gun",
+        "life saver",
+        "cat",
+        "lemon",
+        "liquid soap",
+        "zebra",
+        "duck",
+        "sports car",
+        "giraffe",
+        "pumpkin",
+        "piano",
+        "stop sign",
+        "radiator",
+        "converter",
+        "tissue ",
+        "carrot",
+        "washing machine",
+        "vent",
+        "cookies",
+        "cutting/chopping board",
+        "tennis racket",
+        "candy",
+        "skating and skiing shoes",
+        "scissors",
+        "folder",
+        "baseball",
+        "strawberry",
+        "bow tie",
+        "pigeon",
+        "pepper",
+        "coffee machine",
+        "bathtub",
+        "snowboard",
+        "suitcase",
+        "grapes",
+        "ladder",
+        "pear",
+        "american football",
+        "basketball",
+        "potato",
+        "paint brush",
+        "printer",
+        "billiards",
+        "fire hydrant",
+        "goose",
+        "projector",
+        "sausage",
+        "fire extinguisher",
+        "extension cord",
+        "facial mask",
+        "tennis ball",
+        "chopsticks",
+        "electronic stove and gas stove",
+        "pie",
+        "frisbee",
+        "kettle",
+        "hamburger",
+        "golf club",
+        "cucumber",
+        "clutch",
+        "blender",
+        "tong",
+        "slide",
+        "hot dog",
+        "toothbrush",
+        "facial cleanser",
+        "mango",
+        "deer",
+        "egg",
+        "violin",
+        "marker",
+        "ship",
+        "chicken",
+        "onion",
+        "ice cream",
+        "tape",
+        "wheelchair",
+        "plum",
+        "bar soap",
+        "scale",
+        "watermelon",
+        "cabbage",
+        "router/modem",
+        "golf ball",
+        "pine apple",
+        "crane",
+        "fire truck",
+        "peach",
+        "cello",
+        "notepaper",
+        "tricycle",
+        "toaster",
+        "helicopter",
+        "green beans",
+        "brush",
+        "carriage",
+        "cigar",
+        "earphone",
+        "penguin",
+        "hurdle",
+        "swing",
+        "radio",
+        "CD",
+        "parking meter",
+        "swan",
+        "garlic",
+        "french fries",
+        "horn",
+        "avocado",
+        "saxophone",
+        "trumpet",
+        "sandwich",
+        "cue",
+        "kiwi fruit",
+        "bear",
+        "fishing rod",
+        "cherry",
+        "tablet",
+        "green vegetables",
+        "nuts",
+        "corn",
+        "key",
+        "screwdriver",
+        "globe",
+        "broom",
+        "pliers",
+        "volleyball",
+        "hammer",
+        "eggplant",
+        "trophy",
+        "dates",
+        "board eraser",
+        "rice",
+        "tape measure/ruler",
+        "dumbbell",
+        "hamimelon",
+        "stapler",
+        "camel",
+        "lettuce",
+        "goldfish",
+        "meat balls",
+        "medal",
+        "toothpaste",
+        "antelope",
+        "shrimp",
+        "rickshaw",
+        "trombone",
+        "pomegranate",
+        "coconut",
+        "jellyfish",
+        "mushroom",
+        "calculator",
+        "treadmill",
+        "butterfly",
+        "egg tart",
+        "cheese",
+        "pig",
+        "pomelo",
+        "race car",
+        "rice cooker",
+        "tuba",
+        "crosswalk sign",
+        "papaya",
+        "hair drier",
+        "green onion",
+        "chips",
+        "dolphin",
+        "sushi",
+        "urinal",
+        "donkey",
+        "electric drill",
+        "spring rolls",
+        "tortoise/turtle",
+        "parrot",
+        "flute",
+        "measuring cup",
+        "shark",
+        "steak",
+        "poker card",
+        "binoculars",
+        "llama",
+        "radish",
+        "noodles",
+        "yak",
+        "mop",
+        "crab",
+        "microscope",
+        "barbell",
+        "bread/bun",
+        "baozi",
+        "lion",
+        "red cabbage",
+        "polar bear",
+        "lighter",
+        "seal",
+        "mangosteen",
+        "comb",
+        "eraser",
+        "pitaya",
+        "scallop",
+        "pencil case",
+        "saw",
+        "table tennis paddle",
+        "okra",
+        "starfish",
+        "eagle",
+        "monkey",
+        "durian",
+        "game board",
+        "rabbit",
+        "french horn",
+        "ambulance",
+        "asparagus",
+        "hoverboard",
+        "pasta",
+        "target",
+        "hotair balloon",
+        "chainsaw",
+        "lobster",
+        "iron",
+        "flashlight",
+    )