Metadata-Version: 2.1
Name: sphere-snap
Version: 1.0.3
Summary: A quick and easy to use library for reprojecting various image types
Home-page: https://github.com/androclassic/SphereSnap
Author: Andrei Georgescu
Author-email: andrei.georgescu@yahoo.com
License: MIT License
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Image Processing
Description-Content-Type: text/markdown
Requires-Dist: scipy (>=1.5.1)
Requires-Dist: opencv-python
Requires-Dist: matplotlib
Requires-Dist: numpy
Requires-Dist: logging

# SphereSnap
A quick and easy to use library for reprojecting various image types. (inspired by http://paulbourke.net/panorama/sphere2persp/ ).<br />
The module will use CuPy if detected for accelerating computation. The library can be use simply for reprojecting from one format to another but
also for more sophisticated usecases of manipulating parts of the image or polygons. 


## Examples and usecases
### Reprojecting equirectangular image into pinhole-camera images with customizable FoV and resolution
<img width="727" alt="image" src="https://user-images.githubusercontent.com/1941529/236621219-457eae8c-ad88-452d-8e89-8b16e4750dd1.jpg">
<img width="320" alt="image" src="https://user-images.githubusercontent.com/1941529/236621440-5f2fa7f1-b072-4aff-8596-48b236c1d60f.jpg">

### Create equirectangular image using cubemap faces
<img width="727" alt="image" src="https://user-images.githubusercontent.com/1941529/236621503-b5cf5e22-6a89-41c1-8765-3c5d23c1df1d.png">

### Create fisheye images from equirectangular or cubemap images
<img width="250" alt="image" src="https://user-images.githubusercontent.com/1941529/236621560-cf9f5344-d041-4769-8b86-c52efa2958f6.png">
<img width="500" alt="image" src="https://user-images.githubusercontent.com/1941529/236662589-e4af0d84-319b-4f10-a118-3a296aa33554.png">

### Create top view images from equirectangular/fisheye/planar images
<img width="850" alt="image" src="https://user-images.githubusercontent.com/1941529/236662421-3854c164-b856-4b1e-9447-e997db5713d3.png">

### Correct radially distorted images
<img width="600" alt="image" src="https://user-images.githubusercontent.com/1941529/236621823-a32b57f9-ec4c-4d8c-b45d-f5cda1dbaecc.png">


## How to use it

Module sphere_snap.reprojections contains easy to use functions for simple situations: 
- equi2cubemap
- cubemap2equi
- cubemap2fisheye
- equi2fisheye
- fisheye2equi
- equi2tv

For more complex situtation SphereSnaper can be used which is more flexible

```python
import sphere_snap.utils as snap_utils
import sphere_snap.sphere_coor_projections as sphere_proj
from sphere_snap.snap_config import SnapConfig, ImageProjectionType
from sphere_snap.sphere_snap import SphereSnap
import sphere_snap.reprojections as rpr

```

## Snap to perspective from equirectangular
```python
snap_config = SnapConfig( [0,0,0,1], (1400,1400),(120,120), equi_photo.shape[:2], source_img_type=ImageProjectionType.EQUI)
snap_test = SphereSnap(snap_config)
persp_img = snap_test.snap_to_perspective(equi_photo)
```
## Reproject equirectangular into 6 planar images of 90 degrees FoV (Cubemap)
```python
def get_cube_map_faces(face_size=1440, source_img_hw=(2000,4000), source_img_type=ImageProjectionType.EQUI):

    snap_configs = [SnapConfig( rot(90*i,0), (face_size,face_size),(90,90), source_img_hw, source_img_type=source_img_type)
                        for i in range(4)]
    # top
    snap_configs.append(SnapConfig( rot(0,90), (face_size,face_size),(90,90), source_img_hw, source_img_type=source_img_type))
    # bottom
    snap_configs.append(SnapConfig( rot(0,-90), (face_size,face_size),(90,90), source_img_hw, source_img_type=source_img_type))
    return snap_configs

cube_configs = get_cube_map_faces(face_size=1440, source_img_hw=equi_img.shape[:2])
cube_faces_snaps = [SphereSnap(c) for c in cube_configs]
cumbe_faces_imgs = [snap.snap_to_perspective(equi_img) for snap in cube_faces_snaps]

```
or
```python
cube_faces_imgs = rpr.equi2cubemap(equi_img)
```

## Reproject a planar image into equirectangular
```python
reconstructed_equi = SphereSnap.merge_multiple_snaps((1000,2000), 
                                                     cube_faces_snaps, # snap object specifies destination position
                                                     cumbe_faces_imgs[::-1], # snap image contains planar image pixels
                                                     target_type=ImageProjectionType.EQUI, # destination image type
                                                     merge_method="max")
```
## Reproject a planar image into fisheye 180
```python
reconstructed_fisheye = SphereSnap.merge_multiple_snaps((1000,1000), 
                                                    cube_faces_snaps, # snap object specifies destination position
                                                    cumbe_faces_imgs, # snap image contains planar image pixels
                                                    target_type=ImageProjectionType.FISHEYE_180, # destination image type
                                                    merge_method="max")                                                    
```

## Snap to perspective from fisheye 180
```python
snap_config = SnapConfig( rot(45,1), (1400,1400),(100,100), reconstructed_fisheye.shape[:2], source_img_type=ImageProjectionType.FISHEYE_180)
snap_test = SphereSnap(snap_config)
persp_img = snap_test.snap_to_perspective(reconstructed_fisheye)
```

## Reproject fisheye 180 to equirectangular
```python
snap_configs = [SnapConfig( rot(yaw,pitch), (800,800),(90,90), fisheye180_img.shape[:2], source_img_type=ImageProjectionType.FISHEYE_180) 
                    for yaw,pitch in [[-45,-45],[45,-45],[-45,45],[45,45],[0,0]]]
snaps = [SphereSnap(c) for c in snap_configs]
snap_imgs = [snap.snap_to_perspective(fisheye180_img) for snap in snaps]

reconstructed_equi = SphereSnap.merge_multiple_snaps((1000,2000), 
                                                     snaps, # snap object specifies destination position
                                                     snap_imgs, # snap image contains planar image pixels
                                                     target_type=ImageProjectionType.EQUI, # destination image type
                                                     merge_method="max")

```


