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gene
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In Python the with statement ensures that the file will be closed when leaving the processing therefore your raster is closed ( With statement in Python)

Therefore try:

dst_crs = 'EPSG:4326'
with rasterio.open(result_path + "\\" + "test_infra_{}.tif".format(product_group)) as src:
    transform, width, height = calculate_default_transform(src.crs, dst_crs, src.width, src.height, *src.bounds)
    kwargs = src.meta.copy()
    kwargs.update({'crs': dst_crs, 'transform': transform, 'width': width, 'height': height})
    with rasterio.open(result_path + "\\" + "test_infra_{}_wgs.tif".format(product_group), 'w', **kwargs) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src, i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=transform,
                dst_crs=dst_crs,
                resampling=Resampling.nearest)

and the src raster will not be closed in the second with

In Python the with statement ensures that the file will be closed when leaving the processing therefore your raster is closed ( With statement in Python)

Therefore try:

dst_crs = 'EPSG:4326'
with rasterio.open(result_path + "\\" + "test_infra_{}.tif".format(product_group)) as src:
    transform, width, height = calculate_default_transform(src.crs, dst_crs, src.width, src.height, *src.bounds)
    kwargs = src.meta.copy()
    kwargs.update({'crs': dst_crs, 'transform': transform, 'width': width, 'height': height})
    with rasterio.open(result_path + "\\" + "test_infra_{}_wgs.tif".format(product_group), 'w', **kwargs) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src, i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=transform,
                dst_crs=dst_crs,
                resampling=Resampling.nearest)

In Python the with statement ensures that the file will be closed when leaving the processing therefore your raster is closed ( With statement in Python)

Therefore try:

dst_crs = 'EPSG:4326'
with rasterio.open(result_path + "\\" + "test_infra_{}.tif".format(product_group)) as src:
    transform, width, height = calculate_default_transform(src.crs, dst_crs, src.width, src.height, *src.bounds)
    kwargs = src.meta.copy()
    kwargs.update({'crs': dst_crs, 'transform': transform, 'width': width, 'height': height})
    with rasterio.open(result_path + "\\" + "test_infra_{}_wgs.tif".format(product_group), 'w', **kwargs) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src, i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=transform,
                dst_crs=dst_crs,
                resampling=Resampling.nearest)

and the src raster will not be closed in the second with

Source Link
gene
  • 55.4k
  • 3
  • 113
  • 191

In Python the with statement ensures that the file will be closed when leaving the processing therefore your raster is closed ( With statement in Python)

Therefore try:

dst_crs = 'EPSG:4326'
with rasterio.open(result_path + "\\" + "test_infra_{}.tif".format(product_group)) as src:
    transform, width, height = calculate_default_transform(src.crs, dst_crs, src.width, src.height, *src.bounds)
    kwargs = src.meta.copy()
    kwargs.update({'crs': dst_crs, 'transform': transform, 'width': width, 'height': height})
    with rasterio.open(result_path + "\\" + "test_infra_{}_wgs.tif".format(product_group), 'w', **kwargs) as dst:
        for i in range(1, src.count + 1):
            reproject(
                source=rasterio.band(src, i),
                destination=rasterio.band(dst, i),
                src_transform=src.transform,
                src_crs=src.crs,
                dst_transform=transform,
                dst_crs=dst_crs,
                resampling=Resampling.nearest)