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| from fsspec.parquet import open_parquet_file | |
| import fsspec | |
| import pyarrow.parquet as pq | |
| from .grid import * | |
| import pandas as pd | |
| from io import BytesIO | |
| import os | |
| from PIL import Image | |
| # GLOBAL VARIABLES | |
| if os.path.isfile('helpers/s2l2a_metadata.parquet'): | |
| l2a_meta_path = 'helpers/s2l2a_metadata.parquet' | |
| else: | |
| DATASET_NAME = 'Major-TOM/Core-S2L2A' | |
| l2a_meta_path = 'https://huggingface.co/datasets/{}/resolve/main/metadata.parquet'.format(DATASET_NAME) | |
| if os.path.isfile('helpers/s2l1c_metadata.parquet'): | |
| l1c_meta_path = 'helpers/s2l1c_metadata.parquet' | |
| else: | |
| DATASET_NAME = 'Major-TOM/Core-S2L1C' | |
| l1c_meta_path = 'https://huggingface.co/datasets/{}/resolve/main/metadata.parquet'.format(DATASET_NAME) | |
| grid = Grid(10, latitude_range=(-90,90), longitude_range=(-180,180)) | |
| l2a_df = pd.read_parquet(l2a_meta_path) | |
| l1c_df = pd.read_parquet(l1c_meta_path) | |
| # HELPER FUNCTIONS | |
| def gridcell2ints(grid_string): | |
| up = int(grid_string.split('_')[0][:-1]) * (2*int(grid_string.split('_')[0][-1]=='U') - 1) # +ve if up | |
| right = int(grid_string.split('_')[1][:-1]) * (2*int(grid_string.split('_')[1][-1]=='R') - 1) # +ve if R | |
| return up, right | |
| def row2image(parquet_url, parquet_row, fullrow_read=True): | |
| if fullrow_read: | |
| # option 1 | |
| f=fsspec.open(parquet_url) | |
| temp_path = f.open() | |
| else: | |
| # option 2 | |
| temp_path = open_parquet_file(parquet_url,columns = ["thumbnail"]) | |
| with pq.ParquetFile(temp_path) as pf: | |
| first_row_group = pf.read_row_group(parquet_row, columns=['thumbnail']) | |
| stream = BytesIO(first_row_group['thumbnail'][0].as_py()) | |
| return Image.open(stream) | |
| def row2s2(parquet_url, parquet_row, s2_bands = ["B04", "B03", "B02"]): | |
| with open_parquet_file(parquet_url,columns = s2_bands) as f: | |
| with pq.ParquetFile(f) as pf: | |
| first_row_group = pf.read_row_group(parquet_row, columns=s2_bands) | |
| return first_row_group | |
| def cell2row(grid_string, meta_df, return_row = False): | |
| row_U, col_R = gridcell2ints(grid_string) | |
| R = meta_df.query('grid_row_u == {} & grid_col_r == {}'.format(row_U, col_R)) | |
| if not R.empty: | |
| if return_row: | |
| return R.parquet_url.item(), R.parquet_row.item(), R | |
| else: | |
| return R.parquet_url.item(), R.parquet_row.item() | |
| else: | |
| return None | |
| def map_to_image(map, return_centre=False, return_gridcell=False, l2a=True): | |
| try: | |
| # 1. get bounds | |
| bbox = map.get_bbox() | |
| center = [(bbox[3]+bbox[1])/2, (bbox[2]+bbox[0])/2] | |
| except: | |
| return None | |
| # 2. translate coordinate to major-tom tile | |
| rows, cols = grid.latlon2rowcol([center[0]], [center[1]]) | |
| # 3. translate major-tom cell to row in parquet | |
| df = l2a_df if l2a else l1c_df | |
| row = cell2row("{}_{}".format(rows[0],cols[0]), df, return_row = True) | |
| if row is not None: | |
| parquet_url, parquet_row, meta_row = row | |
| print(meta_row) | |
| img = row2image(parquet_url, parquet_row) | |
| # 4. acquire image # X. update map | |
| lat, lon = meta_row.centre_lat.item(), meta_row.centre_lon.item() | |
| ret = [img] | |
| if return_centre: | |
| ret.append((lat,lon)) | |
| if return_gridcell: | |
| ret.append(meta_row.grid_cell.item()) | |
| return ret | |
| else: | |
| return None |