#891

Committed 24 Sep 2023 05:55PM UTC coverage: 73.57% (+37.0%) from 36.589%

Build # #891

Build Type

push

circleci

Committed by

web-flow

Commit Message

feat: print error msg if creating built-in functions failed (#1204)

Run Details

8991 of 12221 relevant lines covered (73.57%)

0.74 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

0.0

/evadb/functions/ndarray/annotate.py

# coding=utf-8
# Copyright 2018-2023 EvaDB
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
import pandas as pd

from evadb.catalog.catalog_type import NdArrayType
from evadb.functions.abstract.abstract_function import AbstractFunction
from evadb.functions.decorators.decorators import forward, setup
from evadb.functions.decorators.io_descriptors.data_types import PandasDataframe
from evadb.utils.generic_utils import try_to_import_cv2

color = (207, 248, 64)
thickness = 4


class Annotate(AbstractFunction):
    @setup(cacheable=False, function_type="cv2-transformation", batchable=True)
    def setup(self):
        pass

    @property
    def name(self):
        return "Annotate"

    @forward(
        input_signatures=[
            PandasDataframe(
                columns=["data", "labels", "bboxes"],
                column_types=[
                    NdArrayType.FLOAT32,
                    NdArrayType.STR,
                    NdArrayType.FLOAT32,
                ],
                column_shapes=[(None, None, 3), (None,), (None,)],
            )
        ],
        output_signatures=[
            PandasDataframe(
                columns=["annotated_frame_array"],
                column_types=[NdArrayType.FLOAT32],
                column_shapes=[(None, None, 3)],
            )
        ],
    )
    def forward(self, df: pd.DataFrame) -> pd.DataFrame:
        """
        Modify the frame to annotate the bbox on it.

         Returns:
             ret (pd.DataFrame): The modified frame.
        """

        def annotate(row: pd.Series) -> np.ndarray:
            row = row.to_list()
            frame = row[0]
            bboxes = row[2]
            try_to_import_cv2()
            import cv2

            for bbox in bboxes:
                x1, y1, x2, y2 = np.asarray(bbox, dtype="int")
                x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)
                frame = cv2.rectangle(frame, (x1, y1), (x2, y2), color, thickness)
            return frame

        ret = pd.DataFrame()
        ret["annotated_frame_array"] = df.apply(annotate, axis=1)
        return ret

1	# coding=utf-8
2	# Copyright 2018-2023 EvaDB
3	#
4	# Licensed under the Apache License, Version 2.0 (the "License");
5	# you may not use this file except in compliance with the License.
6	# You may obtain a copy of the License at
7	#
8	# http://www.apache.org/licenses/LICENSE-2.0
9	#
10	# Unless required by applicable law or agreed to in writing, software
11	# distributed under the License is distributed on an "AS IS" BASIS,
12	# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
13	# See the License for the specific language governing permissions and
14	# limitations under the License.
15	import numpy as np	×
16	import pandas as pd	×
17
18	from evadb.catalog.catalog_type import NdArrayType	×
19	from evadb.functions.abstract.abstract_function import AbstractFunction	×
20	from evadb.functions.decorators.decorators import forward, setup	×
21	from evadb.functions.decorators.io_descriptors.data_types import PandasDataframe	×
22	from evadb.utils.generic_utils import try_to_import_cv2	×
23
24	color = (207, 248, 64)	×
25	thickness = 4	×
26
27
28	class Annotate(AbstractFunction):	×
29	@setup(cacheable=False, function_type="cv2-transformation", batchable=True)	×
30	def setup(self):	×
31	pass	×
32
33	@property	×
34	def name(self):	×
35	return "Annotate"	×
36
37	@forward(	×
38	input_signatures=[
39	PandasDataframe(
40	columns=["data", "labels", "bboxes"],
41	column_types=[
42	NdArrayType.FLOAT32,
43	NdArrayType.STR,
44	NdArrayType.FLOAT32,
45	],
46	column_shapes=[(None, None, 3), (None,), (None,)],
47	)
48	],
49	output_signatures=[
50	PandasDataframe(
51	columns=["annotated_frame_array"],
52	column_types=[NdArrayType.FLOAT32],
53	column_shapes=[(None, None, 3)],
54	)
55	],
56	)
57	def forward(self, df: pd.DataFrame) -> pd.DataFrame:	×
58	"""
59	Modify the frame to annotate the bbox on it.
60
61	Returns:
62	ret (pd.DataFrame): The modified frame.
63	"""
64
65	def annotate(row: pd.Series) -> np.ndarray:	×
66	row = row.to_list()	×
67	frame = row[0]	×
68	bboxes = row[2]	×
69	try_to_import_cv2()	×
70	import cv2	×
71
72	for bbox in bboxes:	×
73	x1, y1, x2, y2 = np.asarray(bbox, dtype="int")	×
74	x1, y1, x2, y2 = int(x1), int(y1), int(x2), int(y2)	×
75	frame = cv2.rectangle(frame, (x1, y1), (x2, y2), color, thickness)	×
76	return frame	×
77
78	ret = pd.DataFrame()	×
79	ret["annotated_frame_array"] = df.apply(annotate, axis=1)	×
80	return ret	×

georgia-tech-db / eva / #891

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous