Пример #1
0
overlap = params.overlap
datadir = params.download_path

imgs_l = []
dest_base = params.download_path

with Cytomine(host=host, public_key=public_key,
              private_key=private_key) as cytomine:
    res = {}
    annotations = AnnotationCollection()
    annotations.project = id_project
    annotations.showWKT = True
    annotations.showMeta = True
    annotations.showGIS = True
    annotations.showTerm = True
    annotations.showImage = True
    annotations.fetch()
    print(annotations)
    for annotation in annotations:
        print("ID: {} | Img: {} | Pjct: {} | Term: {} ".format(
            annotation.id, annotation.image, annotation.project,
            annotation.term))
        if len(annotation.term) == 1:
            if (annotation.term[0], annotation.image) not in res.keys():
                res[(annotation.term[0], annotation.image)] = []
            res[(annotation.term[0],
                 annotation.image)].append(loads(annotation.location))
            last = res[(annotation.term[0], annotation.image)][-1]
            print(last.bounds, last.to_wkt().count(","))

ks = res.keys()
def get_images_mask_per_annotation_per_user(proj_id, image_id, user_id,
                                            scale_factor, dest):
    im = ImageInstanceCollection()
    im.project = proj_id
    im.image = image_id
    im.fetch_with_filter("project", proj_id)
    image_width = int(im[0].width)
    image_height = int(im[0].height)
    print(image_height, image_width)

    annotations = AnnotationCollection()
    annotations.project = proj_id
    annotations.image = image_id

    annotations.user = user_id
    annotations.showWKT = True
    annotations.showMeta = True
    annotations.showTerm = True
    annotations.showGIS = True
    annotations.showImage = True
    annotations.showUser = True
    annotations.fetch()

    dct_anotations = {}
    for a in annotations:
        print(a.user)
        if len(a.term) == 1:
            term = a.term[0]
            if term not in dct_anotations:
                dct_anotations[term] = []
            dct_anotations[term].append(a.location)
        else:
            warnings.warn("Not suited for multiple or no annotation term")
    for t, lanno in dct_anotations.items():
        result_image = Image.new(mode='1',
                                 size=(int(image_width * scale_factor),
                                       int(image_height * scale_factor)),
                                 color=0)
        for pwkt in lanno:
            if pwkt.startswith("POLYGON"):
                label = "POLYGON"
            elif pwkt.startswith("MULTIPOLYGON"):
                label = "MULTIPOLYGON"

            coordinatesStringList = pwkt.replace(label, '')

            if label == "POLYGON":
                coordinates_string_lists = [coordinatesStringList]
            elif label == "MULTIPOLYGON":
                coordinates_string_lists = coordinatesStringList.split(
                    ')), ((')

                coordinates_string_lists = [
                    coordinatesStringList.replace('(', '').replace(')', '')
                    for coordinatesStringList in coordinates_string_lists
                ]

            for coordinatesStringList in coordinates_string_lists:
                #  create lists of x and y coordinates
                x_coords = []
                y_coords = []
                for point in coordinatesStringList.split(','):
                    point = point.strip(
                        string.whitespace)  # remove leading and ending spaces
                    point = point.strip(
                        string.punctuation
                    )  # Have seen some strings have a ')' at the end so remove it
                    x_coords.append(round(float(point.split(' ')[0])))
                    y_coords.append(round(float(point.split(' ')[1])))

                x_coords_correct_lod = [
                    int(x * scale_factor) for x in x_coords
                ]
                y_coords_correct_lod = [
                    image_height * scale_factor - int(x * scale_factor)
                    for x in y_coords
                ]
                coords = [
                    (i, j)
                    for i, j in zip(x_coords_correct_lod, y_coords_correct_lod)
                ]

                #  draw the polygone in an image and fill it
                ImageDraw.Draw(result_image).polygon(coords, outline=1, fill=1)

        result_image.save(params.dest + '/' + str(t) + '.png')