A sample code for homography image transformation.
| before | after |
|---|---|
 |
 |
Python 2.7
- Numpy
- PIL
This code doesn't depend on OpenCV but only Numpy and PIL, so it can be used on Google App Engine :)
pip install numpy==1.6.1
pip install Pillow==4.3.0
This code might be compatible with upper versions of Numpy/Pillow, but it's not tested.
| base image size | color scale | execution time (avg - 10times) |
|---|---|---|
| 768x1024 | RGB | 14.5ms |
| 768x1024 | Gray | 6.28ms |
| 2448x3264 | RGB | 150ms |
| 2448x3264 | Gray | 60.2ms |
(on Macbook Air)
#!/usr/bin/python
# -*- coding: utf-8 -*-
import path.to.homography as homography
import base64
from io import BytesIO
def some_method_to_process_uploaded_img(base64_img, corner_list, dest_list):
base_img = Image.open(BytesIO(base64.b64decode(base64_img)))
# execute homography transformation
transformed_img = homography.transform(
img=base_img,
crop_corner_list=corner_list,
destination_corner_list=dest_list
)
# or, extend to the size of base_img == (destination_corner_list=None)
# transformed_img = homography.transform(
# img=base_img,
# crop_corner_list=corner_list
# )
# If base64 encoded data is needed:
in_memory_file = BytesIO()
transformed_img.save(in_memory_file, format="PNG")
in_memory_file.seek(0)
img_bytes = in_memory_file.read()
transformed_base64_image = base64.b64encode(img_bytes).decode('ascii')
# execute sample image transformation with ./img/sample.png
test.sh
# transform with gray scale option(-L)
python ./main.py -i ./img/sample.png -c "78, 114, 18, 258, 390, 230, 342, 18" -L
# transform to an intended shape
python ./main.py -i ./img/sample.png -c "78, 114, 18, 258, 390, 230, 342, 18" -d "0, 50, 30, 250, 260, 140, 250, 10"
# save the result as a file
python ./main.py -i ./img/sample.png -c "78, 114, 18, 258, 390, 230, 342, 18" -o ./path/to/destination