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%pylab inline



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%run fix_paths









    



ERROR:root:File `'fix_paths.py'` not found.



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# %load ./srp/data/make_trainval.py
"""Generate train + val splits of the data.

Locations of data are specified in config.py
"""

from srp.config import C
from shapely.strtree import STRtree
import shapely.geometry as sg
import fiona

"""

No 'train' rectangle may overlap a 'val' rectangle.

:param rgb_image_path:
:param volume_raster_path:
:param annotations_path:
:param output_dir:
:param num_folds: The number of folds to generate

Example:

>>> pos, neg = make_sample_meta(output_dir='data/test')

>>> pos.columns
['lon', 'lat', 'box-x', 'box-y', 'box-angle', 'box-length', 'box-width']

The idea is
- `box-x`. `box-y`' is an offset from the sample center. At this point they will always be 0
- `box-angle` is the angle (modulo 90 deg) of the box.
- `box-length` is the length of the box
- `box-width` is the width of the box

This function does NOT do data augmentation or split the data.
It generates a master set of sample metadata.

"""



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rgb_image = C.COLOR.FILE
volume_raster = C.VOLUMETRIC_PATH
annotations_path = C.ANNOTATION_PATH
output_dir = C.INT_DATA
min_separation = C.MIN_SEPARATTION
num_samples = C.NUM_SAMPLES



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class Patch(object):
    def __init__(self):
        super().__init__()
        
        self.x = 0
        self.y = 0
        self.obb = OrientedBoundingBox()
        
        self.rgb = None
        self.vol = None



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p = Patch()
# modify it
puckl.dump(p, filename)



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pickle.load(p)



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# Read in the positive samples
pos_samples = [
    sg.shape(f['geometry']) for f in fiona.open(annotations_path)
]
num_pos = len(pos_samples)









    



---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
<ipython-input-42-7a21e8bab9b7> in <module>()
      1 # Read in the positive samples
      2 pos_samples = [
----> 3     sg.shape(f['geometry']) for f in fiona.open(annotations_path)
      4 ]
      5 num_pos = len(pos_samples)

~/anaconda3/lib/python3.6/site-packages/fiona/__init__.py in open(path, mode, driver, schema, crs, encoding, layer, vfs, enabled_drivers, crs_wkt)
    160                 raise IOError("no such archive file: %r" % archive)
    161         elif path != '-' and not os.path.exists(path):
--> 162             raise IOError("no such file or directory: %r" % path)
    163         c = Collection(path, mode, driver=driver, encoding=encoding,
    164                        layer=layer, vsi=vsi, archive=archive,

OSError: no such file or directory: '/home/femianjc/Projects/srp-boxes/data/raw/srp/box-annotations.geojson'



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# Build a spatial index to test if a new sample is within `min_separation` of
    # an existing positive
    pos_centers = [p.center for p in pos_samples]
    index = STRtree(pos_center)

    # Generate the (centers of) negative samples
    num_neg = num_samples - num_pos

    neg_centers = []
    valid_region = sg.box(*np.r_[np.min(pos_centers, axis=0),
                                 np.max(pos_centers, axis=0)])

    # Read in each shape from the annotations and add a positive sample
    # Make a union of all positive shapes (using shapely)
    # Dilate the union by min_separation
    # randomly select negative points and discard any that fall in the dilated region



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