260 remove classif

.github/workflows/github-actions-ci.yml

@@ -26,4 +26,4 @@ jobs:
           unzip ./data/massachusetts_buildings.zip -d ./data
           python GDL.py mode=sampling
           python GDL.py mode=train
-          python GDL.py mode=inference
+          python GDL.py mode=inference

GDL.py

@@ -2,8 +2,10 @@
 import time
 import hydra
 import logging
+
+from hydra.utils import get_method
 from omegaconf import DictConfig, OmegaConf, open_dict
-from utils.utils import load_obj, print_config, get_git_hash, getpath
+from utils.utils import print_config, get_git_hash
 
 
 @hydra.main(config_path="config", config_name="gdl_config_template")
@@ -45,7 +47,7 @@ def run_gdl(cfg: DictConfig) -> None:
     logging.info('\nOverwritten parameters in the config: \n' + cfg.general.config_override_dirname)
 
     # Start -----------------------------------
-    msg = "Let's start {} for {} !!!".format(cfg.mode, cfg.task.task_name)
+    msg = "Let's start {} for {} !!!".format(cfg.mode, cfg.general.task)
     logging.info(
         "\n" + "-" * len(msg) + "\n" + msg +
         "\n" + "-" * len(msg)
@@ -55,7 +57,7 @@ def run_gdl(cfg: DictConfig) -> None:
     # Start the timer
     start_time = time.time()
     # Read the task and execute it
-    task = load_obj(cfg.task.path_task_function)
+    task = get_method(f"{cfg.mode}_{cfg.general.task}.main")
     task(cfg)
 
     # Add git hash from current commit to parameters.

config/gdl_config_template.yaml

@@ -1,5 +1,4 @@
 defaults:
-  - task: segmentation
   - model: unet
   - training: default_training
   - optimizer: adamw
@@ -20,6 +19,7 @@ general:
   # hydra hijacks working directory by changing it to the current log directory,
   # so it's useful to have this path as a special variable
   # learn more here: https://hydra.cc/docs/next/tutorials/basic/running_your_app/working_directory
+  task: segmentation
   work_dir: ${hydra:runtime.cwd}  # where the code is executed
   config_name: ${hydra:job.config_name}
   config_override_dirname: ${hydra:job.override_dirname}

data/images_to_samples_ci_csv.csv

@@ -1,2 +1,2 @@
-./data/22978945_15.tif,,./data/massachusetts_buildings.gpkg,,trn
-./data/23429155_15.tif,,./data/massachusetts_buildings.gpkg,,tst
+./22978945_15.tif,,./massachusetts_buildings.gpkg,,trn
+./23429155_15.tif,,./massachusetts_buildings.gpkg,,tst

sampling_segmentation.py

@@ -377,7 +377,6 @@ def main(cfg: DictConfig) -> None:
     num_bands = len(cfg.dataset.modalities)
     modalities = read_modalities(cfg.dataset.modalities)  # TODO add the Victor module to manage the modalities
     debug = cfg.debug
-    task = cfg.task.task_name
 
     # RAW DATA PARAMETERS
     # Data folder

train_segmentation.py

@@ -508,14 +508,12 @@ def train(cfg: DictConfig) -> None:
 
     # OPTIONAL PARAMETERS
     debug = get_key_def('debug', cfg)
-    task = get_key_def('task_name',  cfg['task'], default='segmentation')
+    task = get_key_def('task',  cfg['general'], default='segmentation')
     dontcare_val = get_key_def("ignore_index", cfg['dataset'], default=-1)
     bucket_name = get_key_def('bucket_name', cfg['AWS'])
     scale = get_key_def('scale_data', cfg['augmentation'], default=[0, 1])
     batch_metrics = get_key_def('batch_metrics', cfg['training'], default=None)
     crop_size = get_key_def('target_size', cfg['training'], default=None)
-    if task != 'segmentation':
-        raise logging.critical(ValueError(f"\nThe task should be segmentation. The provided value is {task}"))
 
     # MODEL PARAMETERS
     class_weights = get_key_def('class_weights', cfg['dataset'], default=None)

utils/metrics.py

@@ -59,7 +59,7 @@ def report_classification(pred, label, batch_size, metrics_dict, ignore_index=-1
     """Computes precision, recall and f-score for each class and average of all classes.
     http://scikit-learn.org/stable/modules/generated/sklearn.metrics.classification_report.html
     """
-    class_report = classification_report(label.cpu(), pred.cpu(), output_dict=True)
+    class_report = classification_report(label.cpu(), pred.cpu(), output_dict=True, zero_division=1)
 
     class_score = {}
     for key, value in class_report.items():

utils/utils.py

@@ -1,9 +1,7 @@
-import os
 import csv
 import logging
 import numbers
 import subprocess
-import importlib as imp
 from functools import reduce
 from pathlib import Path
 from typing import Sequence, List
@@ -26,7 +24,6 @@
 from rasterio.crs import CRS
 from affine import Affine
 
-from utils.readers import read_parameters
 from urllib.parse import urlparse
 
 try:
@@ -427,7 +424,7 @@ def try2read_csv(path_file, in_case_of_path, msg):
         Path(path_file).resolve(strict=True)
     except FileNotFoundError:
         if in_case_of_path:
-            path_file = os.path.join(in_case_of_path, os.path.basename(path_file))
+            path_file = str(Path(in_case_of_path) / (path_file.split('./')[-1]))
             try:
                 Path(path_file).resolve(strict=True)
             except FileNotFoundError:
@@ -458,8 +455,8 @@ def read_csv(csv_file_name, data_path=None):
             if row[2]:
                 row[2] = try2read_csv(row[2], data_path, 'Gpkg not found:')
             if not isinstance(row[3], str):
-                raise ValueError(f"Attribute name should be a string")
-            if row[3] is not "":
+                logging.error(f"Attribute name should be a string")
+            if row[3] != "":
                 logging.error(f"Deprecation notice:\nFiltering ground truth features by attribute name and values should"
                               f" be done through the dataset parameters in config/dataset. The attribute name value in "
                               f"csv will be ignored. Got: {row[3]}")
@@ -630,26 +627,6 @@ def compare_config_yamls(yaml1: dict, yaml2: dict, update_yaml1: bool = False) -
                     log.info(f'Value in yaml1 updated')
 
 
-def load_obj(obj_path: str, default_obj_path: str = '') -> any:
-    """
-    Extract an object from a given path.
-
-    :param obj_path: (str) Path to an object to be extracted, including the object name.
-    :param default_obj_path: (str) Default path object.
-
-    :return: Extract object. Can be a function or a class or ...
-
-    :raise AttributeError: When the object does not have the given named attribute.
-    """
-    obj_path_list = obj_path.rsplit('.', 1)
-    obj_path = obj_path_list.pop(0) if len(obj_path_list) > 1 else default_obj_path
-    obj_name = obj_path_list[0]
-    module_obj = imp.import_module(obj_path)
-    if not hasattr(module_obj, obj_name):
-        raise AttributeError(f"Object `{obj_name}` cannot be loaded from from `{obj_path}`.")
-    return getattr(module_obj, obj_name)
-
-
 def read_modalities(modalities: str) -> list:
     """
     Function that read the modalities from the yaml and convert it to a list
@@ -696,7 +673,7 @@ def getpath(d, path):
 def print_config(
     config: DictConfig,
     fields: Sequence[str] = (
-        "task",
+        "general.task",
         "mode",
         "dataset",
         "general.work_dir",
@@ -769,14 +746,3 @@ def print_config(
 
     with open("run_config.config", "w") as fp:
         rich.print(tree, file=fp)
-
-
-# def save_useful_info():
-#     shutil.copytree(
-#         os.path.join(hydra.utils.get_original_cwd(), 'src'),
-#         os.path.join(os.getcwd(), 'code/src')
-#     )
-#     shutil.copy2(
-#         os.path.join(hydra.utils.get_original_cwd(), 'hydra_run.py'),
-#         os.path.join(os.getcwd(), 'code')
-#     )