corrected minor things such that everything works well together. Still two existing problems in output/map

detectree2model/predictions/predict.py

@@ -25,7 +25,7 @@ def create_tiles(input_path, tile_width, tile_height, tile_buffer):
     img_path = input_path
     
     current_directory = os.getcwd()
-    tiles_directory = os.path.join(current_directory, "tiles")
+    tiles_directory = os.path.join(current_directory, "tiles/")
     if not os.path.exists(tiles_directory):
         os.makedirs(tiles_directory)
 
@@ -52,7 +52,7 @@ def predict(tile_path, overlap_threshold, confidence_threshold, simplify_value,
     
     download_file(url=url, local_filename=trained_model)
 
-    cfg = setup_cfg(update_model=trained_model)
+    cfg = setup_cfg(update_model=trained_model, out_dir=store_path)
 
     # hash the following line if you have gpu support
     cfg.MODEL.DEVICE = "cpu"
@@ -62,7 +62,7 @@ def predict(tile_path, overlap_threshold, confidence_threshold, simplify_value,
     crowns = stitch_crowns(tile_path + "predictions_geo/", 1)
     clean = clean_crowns(crowns, overlap_threshold, confidence=confidence_threshold)
     clean = clean.set_geometry(clean.simplify(simplify_value))
-    clean.to_file(store_path + "detectree2_delin.geojson")
+    clean.to_file(store_path + "/detectree2_delin.geojson")
 
 def run_detectree2(tif_input_path, store_path, tile_width=20, tile_height=20, tile_buffer=20, overlap_threshold=0.35, confidence_threshold=0.2, simplify_value=0.2): 
     tile_path = create_tiles(input_path=tif_input_path, tile_width=tile_width, tile_height=tile_height, tile_buffer=tile_buffer)

main.py

@@ -42,17 +42,19 @@ 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"
+tif_file_name = "TreeCrownVectorDataset_761588_9673769_20_20_32720.tif"
+tif_input = "/Users/jonathanseele/ETH/Hackathons/EcoHackathon/WeCanopy/test/" + tif_file_name
 
 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_output_df = postprocess(output_directory + '/detectree2_delin.geojson', output_directory + '/processed_delin')
+
 processed_geojson = output_directory + '/processed_delin.geojson'
 
 generate_tree_images(processed_geojson, tif_input)

output/map.ipynb

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:56fbd10c2e7692702cf98b71215b9bf9b3baba674a4fdc6fa99c224513b7b778
-size 3662
+oid sha256:8e257f2bdd28c0df4561a4695a82fc4ee69796d358d0f0d51b3ed407ab3893aa
+size 12819

polygons_processing/postpprocess_detectree2.py

@@ -334,7 +334,7 @@ def export_df_as_geojson(df, filename="output"):
 def convert_id_to_string(prefix, x):
     return prefix + str(x)
 
-def postprocess(prediction_geojson_path):
+def postprocess(prediction_geojson_path, store_path):
     with open(prediction_geojson_path,"r",) as file:
         prediction_data = json.load(file)
 
@@ -351,6 +351,6 @@ def postprocess(prediction_geojson_path):
 
     df_res = process([df])
 
-    export_df_as_geojson(df=df_res, filename="processed_delin")
+    export_df_as_geojson(df=df_res, filename=store_path)
 
     return df_res