How can I fix ValueError: Input shapes do not overlap raster in python?

Question

I want to:

Create a masked version of the input raster where pixels falling within one of the fields are set to 1 and pixels outside the fields are set to 0 then
Reproject the input raster to the provided CRS

Cde:

import fiona
import rasterio
import rasterio.mask
import pycrs


def masked_raster(input_file, raster_file):
    # Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`
    
   
    data = rasterio.open(raster_file)
    

    #creating the a bounding box with Shapely
    ## WGS84 coordinates
    minx, miny = 24.60, 60.00
    maxx, maxy = 25.22, 60.35
    bbox = box(minx, miny, maxx, maxy)

    #inserting the bounding box into GeoDataFrame
    geo = geopandas.GeoDataFrame({'geometry': bbox}, index=[0], crs=from_epsg(4326))

    #Re-project into the same coordinate system as the raster data
    geo = geo.to_crs(crs=data.crs.data)

    #get the coordinates of the geometry in a proper format of rasterio
    def getFeatures(gdf):
      """Function to parse features from GeoDataFrame in such a manner that rasterio wants them"""
      import json
      return [json.loads(gdf.to_json())['features'][0]['geometry']]

    #Getting the geometry coordinates by using the function
    coordinates = getFeatures(geo)
    # mask to clip the raster with the polygon using the coords variable
    out_img, out_transform = mask(data, shapes=coordinates, crop=True)

    out_img = rasterio.open(raster_file).read()
    return out_img

def reproject_raster(raster_file, dst_crs):
    # Reproject the input raster to the provided CRS
    
    src = rasterio.open(raster_file)
    
    # Parse EPSG code
    epsg_code = int(data.crs.data['init'][5:])

    #copy metadata
    out_meta = raster_file.meta.copy()
    #update the metadata with new dimensions, transform (affine) and CRS 
    out_meta.update({"driver": "GTiff", "height": out_img.shape[1], "width": out_img.shape[2], "transform": out_transform, "crs": pycrs.parser.from_epsg_code(epsg_code).to_proj4()})

    #save the clipped raster to disk
    with rasterio.open(out_tif, "w", **out_meta) as dst:
      dst.write(out_img)


    dst = src
    
    return dst

# Run this to validate your function works correctly

assert masked_raster('crops.geojson', 'crops.tif')[0].sum() == 1144636.0, "Sorry wrong answer"
assert str(reproject_raster('crops.tif', 'EPSG:4326').crs) == 'EPSG:4326', "Sorry wrong answer"
print("Congratulations, all is working just fine !!!")

Error:

Git Repo Link

Please proofread after posting (edited). And what exactly has this to do with machine-learning? — desertnaut
– desertnaut, Commented Mar 14, 2021 at 19:07

spchaane · Accepted Answer · 2021-03-14 19:14:23Z

Thanks guys, I managed to find the solution to my error: "rasterio.tools.mask.mask (in more recent versions, it is rasterio.mask.mask) includes an option invert. When invert=True, the mask will be applied to pixels that overlap your shape, rather than areas outside the shape"

So I changed:

out_img, out_transform = mask(data, shapes=coordinates, crop=True)

To:

out_img, out_transform = mask(src, geoms, invert=True)

The error is fixed. Here is the full code I rewrote. Though I am not getting the expected output by there is no error, its only the part where it must meet the assertion requirements that must be fixed.

def masked_raster(input_file, raster_file):
    # Create a masked version of the input raster where pixels falling within one of the fields are set to `1` and pixels outside the fields are set to `0`
    
   
    # the polygon GeoJSON geometry
    geoms = [{'type': 'Polygon', 'coordinates': [[(250204.0, 141868.0), (250942.0, 141868.0), (250942.0, 141208.0), (250204.0, 141208.0), (250204.0, 141868.0)]]}]
    # load the raster, mask it by the polygon and crop it
    with rasterio.open("crops.tif") as src:
        out_img, out_transform = mask(src, geoms, invert=True)
    out_meta = src.meta.copy()

    # save the resulting raster  
    out_meta.update({"driver": "GTiff",
    "height": out_image.shape[1],
    "width": out_image.shape[2],
    "transform": out_transform})

    
    return out_img

def reproject_raster(raster_file, dst_crs):
    # Reproject the input raster to the provided CRS
    
    with rasterio.open("masked.tif", "w", **out_meta) as dst:
      dst.write(out_image)


    dst = src
    
    return dst

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