Feature/issue 144 replace typer with fire for comand line args

README.md

@@ -87,7 +87,7 @@ The design of anchors is critical for the performance of one-stage detectors. Py
 ```bash
 pyodi train-config generation \
   $TINY_COCO_ANIMAL/annotations/train.json \
-  --input-size 1280 720 \
+  --input-size [1280,720] \
   --n-ratios 3 --n-scales 3
 ```
 
@@ -101,7 +101,7 @@ Pyodi evaluation app has been designed with the aim of providing a simple tool t
 pyodi train-config evaluation \
   $TINY_COCO_ANIMAL/annotations/train.json \
   $TINY_COCO_ANIMAL/resources/anchor_config.py \
-  --input-size 1280 720
+  --input-size [1280,720]
 ```
 
 ![Anchor overlap plot](docs/images/train-config-evaluation/overlap.png)

pyodi/apps/coco/__init__.py

@@ -1,13 +1,8 @@
-import typer
-
 from pyodi.apps.coco.coco_merge import coco_merge
 from pyodi.apps.coco.coco_split import property_split, random_split
 
-coco_app = typer.Typer()
-coco_app.command("merge")(coco_merge)
-coco_app.command("random-split")(random_split)
-coco_app.command("property-split")(property_split)
-
-
-if __name__ == "__main__":
-    coco_app()
+coco_app = {
+    "merge": coco_merge,
+    "random-split": random_split,
+    "property-split": property_split,
+}

pyodi/apps/coco/coco_merge.py

@@ -18,14 +18,10 @@
 import json
 from typing import Any, Dict
 
-import typer
 from loguru import logger
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def coco_merge(input_extend: str, input_add: str, output_file: str,) -> str:
     """Merge COCO annotation files.
 

pyodi/apps/coco/coco_split.py

@@ -48,14 +48,10 @@
 from typing import List
 
 import numpy as np
-import typer
 from loguru import logger
 
-app = typer.Typer()
-
 
 @logger.catch  # noqa: C901
-@app.command()
 def property_split(
     annotations_file: str, output_filename: str, split_config_file: str,
 ) -> List[str]:
@@ -160,7 +156,6 @@ def property_split(
 
 
 @logger.catch
-@app.command()
 def random_split(
     annotations_file: str,
     output_filename: str,

pyodi/apps/crops/__init__.py

@@ -1,12 +1,7 @@
-import typer
-
 from pyodi.apps.crops.crops_merge import crops_merge
 from pyodi.apps.crops.crops_split import crops_split
 
-crops_app = typer.Typer()
-crops_app.command("merge")(crops_merge)
-crops_app.command("split")(crops_split)
-
-
-if __name__ == "__main__":
-    crops_app()
+crops_app = {
+    "merge": crops_merge,
+    "split": crops_split,
+}

pyodi/apps/crops/crops_merge.py

@@ -8,16 +8,12 @@
 from pathlib import Path
 from typing import Optional
 
-import typer
 from loguru import logger
 
 from pyodi.core.nms import nms_predictions
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def crops_merge(
     ground_truth_file: str,
     output_file: str,
@@ -103,7 +99,3 @@ def crops_merge(
         json.dump(new_ground_truth, f, indent=2)
 
     return output_file
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/crops/crops_split.py

@@ -9,7 +9,6 @@
 from pathlib import Path
 from typing import Dict, List
 
-import typer
 from loguru import logger
 from PIL import Image
 
@@ -20,11 +19,8 @@
     get_crops_corners,
 )
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def crops_split(
     ground_truth_file: str,
     image_folder: str,
@@ -114,7 +110,3 @@ def crops_split(
 
     with open(output_file, "w") as f:
         json.dump(new_ground_truth, f, indent=2)
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/evaluation.py

@@ -35,17 +35,13 @@
 import re
 from typing import Optional
 
-import typer
 from loguru import logger
 from pycocotools.cocoeval import COCOeval
 
 from pyodi.core.utils import load_coco_ground_truth_from_StringIO
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def evaluation(
     ground_truth_file: str, predictions_file: str, string_to_match: Optional[str] = None
 ) -> None:
@@ -79,7 +75,3 @@ def evaluation(
     coco_eval.evaluate()
     coco_eval.accumulate()
     coco_eval.summarize()
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/ground_truth.py

@@ -48,7 +48,6 @@
 from pathlib import Path
 from typing import Optional, Tuple
 
-import typer
 from loguru import logger
 
 from pyodi.core.boxes import add_centroids
@@ -60,11 +59,8 @@
 from pyodi.plots.boxes import get_centroids_heatmap, plot_heatmap
 from pyodi.plots.common import plot_scatter_with_histograms
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def ground_truth(
     ground_truth_file: str,
     show: bool = True,
@@ -131,7 +127,3 @@ def ground_truth(
         output=output,
         output_size=output_size,
     )
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/paint_annotations.py

@@ -26,19 +26,15 @@
 from typing import Dict, Optional
 
 import numpy as np
-import typer
 from loguru import logger
 from matplotlib import cm as cm
 from matplotlib import pyplot as plt
 from matplotlib.collections import PatchCollection
 from matplotlib.patches import Polygon
 from PIL import Image
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def paint_annotations(
     ground_truth_file: str,
     image_folder: str,
@@ -165,7 +161,3 @@ def paint_annotations(
 
             plt.savefig(output_file)
             plt.close()
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/train_config/__init__.py

@@ -1,12 +1,7 @@
-import typer
-
 from pyodi.apps.train_config.train_config_evaluation import train_config_evaluation
 from pyodi.apps.train_config.train_config_generation import train_config_generation
 
-train_config_app = typer.Typer()
-train_config_app.command("evaluation")(train_config_evaluation)
-train_config_app.command("generation")(train_config_generation)
-
-
-if __name__ == "__main__":
-    train_config_app()
+train_config_app = {
+    "generation": train_config_generation,
+    "evaluation": train_config_evaluation,
+}

pyodi/apps/train_config/train_config_evaluation.py

@@ -21,7 +21,7 @@
 pyodi train-config evaluation \\
 $TINY_COCO_ANIMAL/annotations/train.json \\
 $TINY_COCO_ANIMAL/resources/anchor_config.py \\
---input-size 1280 720
+--input-size [1280,720]
 ```
 
 The app provides four different plots:
@@ -74,7 +74,6 @@
 from typing import Any, Dict, Optional, Tuple
 
 import numpy as np
-import typer
 from loguru import logger
 
 from pyodi.core.anchor_generator import AnchorGenerator
@@ -92,8 +91,6 @@
 )
 from pyodi.plots.evaluation import plot_overlap_result
 
-app = typer.Typer()
-
 
 def load_anchor_config_file(anchor_config_file: str) -> Dict[str, Any]:
     """Loads the `anchor_config_file`.
@@ -122,11 +119,10 @@ def load_anchor_config_file(anchor_config_file: str) -> Dict[str, Any]:
 
 
 @logger.catch
-@app.command()
 def train_config_evaluation(
     ground_truth_file: str,
     anchor_config: str,
-    input_size: Tuple[int, int] = (1333, 800),
+    input_size: Tuple[int, int] = (1280, 720),
     show: bool = True,
     output: Optional[str] = None,
     output_size: Tuple[int, int] = (1600, 900),
@@ -212,7 +208,3 @@ def train_config_evaluation(
     plot_overlap_result(
         df_annotations, show=show, output=output, output_size=output_size
     )
-
-
-if __name__ == "__main__":
-    app()

pyodi/apps/train_config/train_config_generation.py

@@ -33,7 +33,7 @@
 ```bash
 pyodi train-config generation \\
 $TINY_COCO_ANIMAL/annotations/train.json \\
---input-size 1280 720 \\
+--input-size [1280,720] \\
 --n-ratios 3 --n-scales 3
 ```
 
@@ -54,7 +54,7 @@
 the number of anchors is goint to increase, which will influence training computational cost.
 
 ```bash
-pyodi train-config generation annotations/train.json --input-size 1280 720 --n-ratios 4 --n-scales 3
+pyodi train-config generation annotations/train.json --input-size [1280,720] --n-ratios 4 --n-scales 3
 ```
 
 In plot below we can observe the result for `n_ratios` equal to four.
@@ -101,10 +101,8 @@
 from typing import List, Optional, Tuple
 
 import numpy as np
-import typer
 from loguru import logger
 
-from pyodi.apps.train_config.train_config_evaluation import train_config_evaluation
 from pyodi.core.anchor_generator import AnchorGenerator
 from pyodi.core.boxes import (
     filter_zero_area_bboxes,
@@ -120,23 +118,19 @@
 )
 from pyodi.plots.clustering import plot_clustering_results
 
-app = typer.Typer()
-
 
 @logger.catch
-@app.command()
 def train_config_generation(
     ground_truth_file: str,
     input_size: Tuple[int, int] = (1280, 720),
     n_ratios: int = 3,
     n_scales: int = 3,
-    strides: Optional[List[int]] = typer.Argument(None),
-    base_sizes: Optional[List[int]] = typer.Argument(None),
+    strides: Optional[List[int]] = None,
+    base_sizes: Optional[List[int]] = None,
     show: bool = True,
     output: Optional[str] = None,
     output_size: Tuple[int, int] = (1600, 900),
     keep_ratio: bool = False,
-    evaluate: bool = True,
 ) -> AnchorGenerator:
     """Computes optimal anchors for a given COCO dataset based on iou clustering.
 
@@ -152,9 +146,6 @@ def train_config_generation(
         output: Output file where results are saved. Defaults to None.
         output_size: Size of saved images. Defaults to (1600, 900).
         keep_ratio: Whether to keep the aspect ratio or not. Defaults to False.
-        evaluate: Whether to evaluate or not the anchors. Check
-            [`pyodi train-config evaluation`][pyodi.apps.train_config.train_config_evaluation.train_config_evaluation]
-            for more information.
 
     Returns:
         Anchor generator instance.
@@ -230,20 +221,4 @@ def train_config_generation(
         with open(output_file, "w") as f:
             f.write(anchor_generator.to_string())
 
-    if evaluate:
-
-        anchor_config = dict(anchor_generator=anchor_generator.to_dict())
-        train_config_evaluation(
-            ground_truth_file=ground_truth_file,
-            anchor_config=anchor_config,  # type: ignore
-            input_size=input_size,
-            show=show,
-            output=output,
-            output_size=output_size,
-        )
-
     return anchor_generator
-
-
-if __name__ == "__main__":
-    app()