Delete harmonize.py

harmonize.py

@@ -1,56 +0,0 @@
-
-from rasterio.enums import Resampling
-from huggingface_hub import hf_hub_download
-import pandas as pd
-import rasterio
-import matplotlib.pyplot as plt
-
-df = pd.read_excel('out.xlsx')
-
-records = []
-for index, row in df.iterrows():
-    if row['crs'] == '+proj=longlat +datum=WGS84 +no_defs=True':
-        records.append(row)
-
-for record in records:
-
-    hf_hub_download(
-        'fedric95/umbra', 
-        './image/{id}.tiff'.format(id=record['id']),
-        local_dir = 'dataset/',
-        repo_type = 'dataset'
-    )
-    hf_hub_download(
-        'fedric95/umbra', 
-        './label/{id}.tiff'.format(id=record['id']),
-        local_dir = 'dataset/',
-        repo_type = 'dataset'
-    )
-
-    image = './dataset/image/{id}.tiff'.format(id=record['id'])
-    label = './dataset/label/{id}.tiff'.format(id=record['id'])
-
-    with rasterio.open(image) as image_src:
-        with rasterio.open(label) as label_src:
-            
-            # resample data to target shape
-            data = label_src.read(
-                out_shape=(
-                    label_src.count,
-                    image_src.height,
-                    image_src.width
-                ),
-                resampling=Resampling.bilinear
-            )
-
-            # scale image transform
-            transform = label_src.transform * label_src.transform.scale(
-                (label_src.width / data.shape[-1]),
-                (label_src.height / data.shape[-2])
-            )
-
-            import pdb
-            pdb.set_trace()
-
-        plt.imshow(data[0, :, :])
-        plt.savefig('label.png')