Last commit not found
| from detectree2model.predictions.predict import run_detectree2 | |
| from polygons_processing.postpprocess_detectree2 import postprocess | |
| from generate_tree_images.generate_tree_images import generate_tree_images | |
| from classification.classification_predict import classify | |
| import os | |
| import json | |
| def row_to_feature(row): | |
| feature = { | |
| "id": row["id"], | |
| "type": "Feature", | |
| "properties": {"Confidence_score": row["Confidence_score"]}, | |
| "geometry": {"type": "Polygon", "coordinates": [row["coordinates"]]}, | |
| "species": row['species'] | |
| } | |
| return feature | |
| def export_geojson(df, filename): | |
| features = [row_to_feature(row) for idx, row in df.iterrows()] | |
| feature_collection = { | |
| "type": "FeatureCollection", | |
| "crs": {"type": "name", "properties": {"name": "urn:ogc:def:crs:EPSG::32720"}}, | |
| "features": features, | |
| } | |
| output_geojson = json.dumps(feature_collection) | |
| with open(f"{filename}.geojson", "w") as f: | |
| f.write(output_geojson) | |
| print(f"GeoJSON data exported to '{filename}.geojson' file.") | |
| """ | |
| tif_input: the file containing a tif that we are analyzing | |
| tif_file_name: the file name of the tif input. tif_input is the folder in which the tif file lies | |
| (detectree2 works with that) but generate_tree_images requires path including the file hence the file name is needed | |
| output_directory: the directory were all in-between and final files are stored | |
| generate_tree_images stores the cutout tree images in a separate folder | |
| """ | |
| tif_input = "/Users/jonathanseele/ETH/Hackathons/EcoHackathon/WeCanopy/test/" | |
| tif_file_name = "TreeCrownVectorDataset_761588_9673769_20_20_32720" | |
| current_directory = os.getcwd() | |
| output_directory = os.path.join(current_directory, "outputs") | |
| if not os.path.exists(output_directory): | |
| os.makedirs(output_directory) | |
| run_detectree2(tif_input, store_path=output_directory) | |
| processed_output_df = postprocess(output_directory + '/detectree2_delin.geojson') | |
| processed_geojson = output_directory + '/processed_delin.geojson' | |
| generate_tree_images(processed_geojson, tif_input) | |
| output_folder = './tree_images' | |
| all_top_3_list = [] # Initialize an empty list to accumulate all top_3 lists | |
| for file_name in os.listdir(output_folder): | |
| file_path = os.path.join(output_folder, file_name) | |
| probs = classify(file_path) | |
| top_3 = probs.head(3) | |
| top_3_list = [[cls, prob] for cls, prob in top_3.items()] | |
| # Accumulate the top_3_list for each file | |
| all_top_3_list.append(top_3_list) | |
| # Assign the accumulated top_3_list to the 'species' column of the dataframe | |
| processed_output_df['species'] = all_top_3_list | |
| final_output_path = 'result' | |
| export_geojson(processed_output_df, final_output_path) | |