utils/refer.py

__author__ = "licheng"

"""
This interface provides access to four datasets:
1) refclef
2) refcoco
3) refcoco+
4) refcocog
split by unc and google

The following API functions are defined:
REFER      - REFER api class
getRefIds  - get ref ids that satisfy given filter conditions.
getAnnIds  - get ann ids that satisfy given filter conditions.
getImgIds  - get image ids that satisfy given filter conditions.
getCatIds  - get category ids that satisfy given filter conditions.
loadRefs   - load refs with the specified ref ids.
loadAnns   - load anns with the specified ann ids.
loadImgs   - load images with the specified image ids.
loadCats   - load category names with the specified category ids.
getRefBox  - get ref's bounding box [x, y, w, h] given the ref_id
showRef    - show image, segmentation or box of the referred object with the ref
getMask    - get mask and area of the referred object given ref
showMask   - show mask of the referred object given ref
"""

import itertools
import json
import os.path as osp
import pickle
import sys
import time
from pprint import pprint

import matplotlib.pyplot as plt
import numpy as np
import skimage.io as io
from matplotlib.collections import PatchCollection
from matplotlib.patches import Polygon, Rectangle
from pycocotools import mask


class REFER:
    def __init__(self, data_root, dataset="refcoco", splitBy="unc"):
                                                                                         
                                                           
                                                    
        print("loading dataset %s into memory..." % dataset)
        self.ROOT_DIR = osp.abspath(osp.dirname(__file__))
        self.DATA_DIR = osp.join(data_root, dataset)
        if dataset in ["refcoco", "refcoco+", "refcocog"]:
            self.IMAGE_DIR = osp.join(data_root, "images/mscoco/images/train2014")
        elif dataset == "refclef":
            self.IMAGE_DIR = osp.join(data_root, "images/saiapr_tc-12")
        elif dataset == 'rs_reason' or dataset == 'rrsisd':
            self.IMAGE_DIR = osp.join(data_root, "images/rrsisd/JPEGImages")
        else:
            print("No refer dataset is called [%s]" % dataset)
            sys.exit()

        self.dataset = dataset

                                                        
        tic = time.time()

        ref_file = osp.join(self.DATA_DIR,"refs(" + splitBy + ").p")
                                       
        self.data = {}
        self.data["dataset"] = dataset
        self.data["refs"] = pickle.load(open(ref_file, "rb"))

                                                           
        instances_file = osp.join(self.DATA_DIR, "instances.json")
        instances = json.load(open(instances_file, "rb"))
        self.data["images"] = instances["images"]
        self.data["annotations"] = instances["annotations"]
        self.data["categories"] = instances["categories"]

                      
        self.createIndex()
        print("DONE (t=%.2fs)" % (time.time() - tic))

    def createIndex(self):
                                
                                    
                                    
                                        
                                                   
                                         
                                          
                                          
                                       
                                       
                                             
                                        
                                             
        print("creating index...")
                                   
        Anns, Imgs, Cats, imgToAnns = {}, {}, {}, {}
        for ann in self.data["annotations"]:
            Anns[ann["id"]] = ann
            imgToAnns[ann["image_id"]] = imgToAnns.get(ann["image_id"], []) + [ann]
        for img in self.data["images"]:
            Imgs[img["id"]] = img
        for cat in self.data["categories"]:
            Cats[cat["id"]] = cat["name"]

                              
        Refs, imgToRefs, refToAnn, annToRef, catToRefs = {}, {}, {}, {}, {}
        Sents, sentToRef, sentToTokens = {}, {}, {}
        for ref in self.data["refs"]:
                 
            ref_id = ref["ref_id"]
            ann_id = ref["ann_id"]
            category_id = ref["category_id"]
            image_id = ref["image_id"]

                                        
            Refs[ref_id] = ref
            imgToRefs[image_id] = imgToRefs.get(image_id, []) + [ref]
            catToRefs[category_id] = catToRefs.get(category_id, []) + [ref]
            refToAnn[ref_id] = Anns[ann_id]
            annToRef[ann_id] = ref

                                 
            for sent in ref["sentences"]:
                Sents[sent["sent_id"]] = sent
                sentToRef[sent["sent_id"]] = ref
                sentToTokens[sent["sent_id"]] = sent["tokens"]

                              
        self.Refs = Refs
        self.Anns = Anns
        self.Imgs = Imgs
        self.Cats = Cats
        self.Sents = Sents
        self.imgToRefs = imgToRefs
        self.imgToAnns = imgToAnns
        self.refToAnn = refToAnn
        self.annToRef = annToRef
        self.catToRefs = catToRefs
        self.sentToRef = sentToRef
        self.sentToTokens = sentToTokens
        print("index created.")

    def getRefIds(self, image_ids=[], cat_ids=[], ref_ids=[], split=""):
        image_ids = image_ids if type(image_ids) == list else [image_ids]
        cat_ids = cat_ids if type(cat_ids) == list else [cat_ids]
        ref_ids = ref_ids if type(ref_ids) == list else [ref_ids]

        if len(image_ids) == len(cat_ids) == len(ref_ids) == len(split) == 0:
            refs = self.data["refs"]
        else:
            if not len(image_ids) == 0:
                refs = [self.imgToRefs[image_id] for image_id in image_ids]
            else:
                refs = self.data["refs"]
            if not len(cat_ids) == 0:
                refs = [ref for ref in refs if ref["category_id"] in cat_ids]
            if not len(ref_ids) == 0:
                refs = [ref for ref in refs if ref["ref_id"] in ref_ids]
            if not len(split) == 0:
                if split in ["testA", "testB", "testC"]:
                    refs = [
                        ref for ref in refs if split[-1] in ref["split"]
                    ]                                        
                elif split in ["testAB", "testBC", "testAC"]:
                    refs = [
                        ref for ref in refs if ref["split"] == split
                    ]                          
                elif split == "test":
                    refs = [ref for ref in refs if "test" in ref["split"]]
                elif split == "train" or split == "val":
                    refs = [ref for ref in refs if ref["split"] == split]
                else:
                    print("No such split [%s]" % split)
                    sys.exit()
        ref_ids = [ref["ref_id"] for ref in refs]
        return ref_ids

    def getAnnIds(self, image_ids=[], cat_ids=[], ref_ids=[]):
        image_ids = image_ids if type(image_ids) == list else [image_ids]
        cat_ids = cat_ids if type(cat_ids) == list else [cat_ids]
        ref_ids = ref_ids if type(ref_ids) == list else [ref_ids]

        if len(image_ids) == len(cat_ids) == len(ref_ids) == 0:
            ann_ids = [ann["id"] for ann in self.data["annotations"]]
        else:
            if not len(image_ids) == 0:
                lists = [
                    self.imgToAnns[image_id]
                    for image_id in image_ids
                    if image_id in self.imgToAnns
                ]                  
                anns = list(itertools.chain.from_iterable(lists))
            else:
                anns = self.data["annotations"]
            if not len(cat_ids) == 0:
                anns = [ann for ann in anns if ann["category_id"] in cat_ids]
            ann_ids = [ann["id"] for ann in anns]
            if not len(ref_ids) == 0:
                ids = set(ann_ids).intersection(
                    set([self.Refs[ref_id]["ann_id"] for ref_id in ref_ids])
                )
        return ann_ids

    def getImgIds(self, ref_ids=[]):
        ref_ids = ref_ids if type(ref_ids) == list else [ref_ids]

        if not len(ref_ids) == 0:
            image_ids = list(set([self.Refs[ref_id]["image_id"] for ref_id in ref_ids]))
        else:
            image_ids = self.Imgs.keys()
        return image_ids

    def getCatIds(self):
        return self.Cats.keys()

    def loadRefs(self, ref_ids=[]):
        if type(ref_ids) == list:
            return [self.Refs[ref_id] for ref_id in ref_ids]
        elif type(ref_ids) == int:
            return [self.Refs[ref_ids]]

    def loadAnns(self, ann_ids=[]):
        if type(ann_ids) == list:
            return [self.Anns[ann_id] for ann_id in ann_ids]
        elif type(ann_ids) == int or type(ann_ids) == unicode:
            return [self.Anns[ann_ids]]

    def loadImgs(self, image_ids=[]):
        if type(image_ids) == list:
            return [self.Imgs[image_id] for image_id in image_ids]
        elif type(image_ids) == int:
            return [self.Imgs[image_ids]]

    def loadCats(self, cat_ids=[]):
        if type(cat_ids) == list:
            return [self.Cats[cat_id] for cat_id in cat_ids]
        elif type(cat_ids) == int:
            return [self.Cats[cat_ids]]

    def getRefBox(self, ref_id):
        ref = self.Refs[ref_id]
        ann = self.refToAnn[ref_id]
        return ann["bbox"]                

    def showRef(self, ref, seg_box="seg"):
        ax = plt.gca()
                    
        image = self.Imgs[ref["image_id"]]
        I = io.imread(osp.join(self.IMAGE_DIR, image["file_name"]))
        ax.imshow(I)
                               
        for sid, sent in enumerate(ref["sentences"]):
            print("%s. %s" % (sid + 1, sent["sent"]))
                            
        if seg_box == "seg":
            ann_id = ref["ann_id"]
            ann = self.Anns[ann_id]
            polygons = []
            color = []
            c = "none"
            if type(ann["segmentation"][0]) == list:
                                           
                for seg in ann["segmentation"]:
                    poly = np.array(seg).reshape((len(seg) / 2, 2))
                    polygons.append(Polygon(poly, True, alpha=0.4))
                    color.append(c)
                p = PatchCollection(
                    polygons,
                    facecolors=color,
                    edgecolors=(1, 1, 0, 0),
                    linewidths=3,
                    alpha=1,
                )
                ax.add_collection(p)                        
                p = PatchCollection(
                    polygons,
                    facecolors=color,
                    edgecolors=(1, 0, 0, 0),
                    linewidths=1,
                    alpha=1,
                )
                ax.add_collection(p)                    
            else:
                                       
                rle = ann["segmentation"]
                m = mask.decode(rle)
                img = np.ones((m.shape[0], m.shape[1], 3))
                color_mask = np.array([2.0, 166.0, 101.0]) / 255
                for i in range(3):
                    img[:, :, i] = color_mask[i]
                ax.imshow(np.dstack((img, m * 0.5)))
                           
        elif seg_box == "box":
            ann_id = ref["ann_id"]
            ann = self.Anns[ann_id]
            bbox = self.getRefBox(ref["ref_id"])
            box_plot = Rectangle(
                (bbox[0], bbox[1]),
                bbox[2],
                bbox[3],
                fill=False,
                edgecolor="green",
                linewidth=3,
            )
            ax.add_patch(box_plot)

    def getMask(self, ref):
                                           
        ann = self.refToAnn[ref["ref_id"]]
        image = self.Imgs[ref["image_id"]]
        if type(ann["segmentation"][0]) == list:           
            rle = mask.frPyObjects(ann["segmentation"], image["height"], image["width"])
        else:
            rle = ann["segmentation"]
        m = mask.decode(rle)
        m = np.sum(
            m, axis=2
        )                                                                            
        m = m.astype(np.uint8)                       
                      
        area = sum(mask.area(rle))                                  
        return {"mask": m, "area": area}
                    
                                                                                                   
                                                                                                   
                                                                                   
                                                 
                                        
                              
                                                                                     
                                              
                                                  
               
                                                  
                                                                                 
                                    
                                                 
                                              
                                                    
                                                                                                       
                                    
                                                                  
                                       
                                      
                   
                                                                                                                                  
                               
                                                                     
                      
                       
                        
                                                      
                                                      
                            
                                        
                                              
                    

    def showMask(self, ref):
        M = self.getMask(ref)
        msk = M["mask"]
        ax = plt.gca()
        ax.imshow(msk)


if __name__ == "__main__":
    refer = REFER(dataset="refcocog", splitBy="google")
    ref_ids = refer.getRefIds()
    print(len(ref_ids))

    print(len(refer.Imgs))
    print(len(refer.imgToRefs))

    ref_ids = refer.getRefIds(split="train")
    print("There are %s training referred objects." % len(ref_ids))

    for ref_id in ref_ids:
        ref = refer.loadRefs(ref_id)[0]
        if len(ref["sentences"]) < 2:
            continue

        pprint(ref)
        print("The label is %s." % refer.Cats[ref["category_id"]])
        plt.figure()
        refer.showRef(ref, seg_box="box")
        plt.show()