Handle all zoom values (#14)

Provide a `--zoom` argument to rescale images according to zoom.

README.md

@@ -29,6 +29,10 @@ At inference time, navigate to the directory you want to run predictions on. The
 - `python -m acrosome_counter . --infer` to produce predictions. You may also add `--plot` to plot the results during execution.
 - `python -m acrosome_counter . --review` to review the predictions produced previously. You may also use `python -m acrosome_counter . --infer --review` to automatically fall into review mode after inference.
 
+You may also use `-t` or `--threshold` to filter results according to confidence. For instance, `python -m acrosome_counter . --infer --review -t 0.2` would discard all predictions with confidence under `0.2`. Threshold ranges from `0` to `1` and is `0.1` by default.
+
+You may also use `-z` or `--zoom` if your input images have a zoom different from 20 ×. For instance, `python -m acrosome_counter . --infer --review --zoom 40` would resize images at 40 × magnification to the appropriate 20 ×.
+
 `acrosome-counter` saves predictions as a XML file under the current directory (`.`) and statistics as a CSV file. The XML file is compatible with [CVAT](https://github.com/openvinotoolkit/cvat). The CSV file can be opened from any software that can parse tabular data, such as Microsoft Excel.
 
 

acrosome_counter/__main__.py

@@ -7,7 +7,7 @@
 from acrosome_counter.load_dataset import Dataset
 from acrosome_counter.build_model import build_cfg
 from acrosome_counter.train import Trainer
-from acrosome_counter.predict import Predictor
+from acrosome_counter.predict import Predictor, adjust_zoom
 
 
 def main(args):
@@ -29,6 +29,7 @@ def main(args):
             is_training, args.batch_size, args.learning_rate, args.qty_iters,
         )
         cfg.MODEL.ROI_HEADS.SCORE_THRESH_TEST = args.threshold
+        adjust_zoom(cfg, args.zoom)
         predictor = Predictor(cfg)
         predictor(dataset, plot=args.plot)
         predictor.export_xml()
@@ -46,6 +47,7 @@ def main(args):
     parser.add_argument('-it', '--qty_iters', default=1, type=int)
     parser.add_argument('-lr', '--learning_rate', default=2.5E-4, type=float)
     parser.add_argument('-t', '--threshold', default=.1, type=float)
+    parser.add_argument('-z', '--zoom', default=20, type=float)
     parser.add_argument('--train', action='store_true')
     parser.add_argument('--infer', action='store_true')
     parser.add_argument('--plot', action='store_true')

acrosome_counter/predict.py

@@ -14,6 +14,8 @@
 
 mpl.use('TkAgg')
 
+DEFAULT_ZOOM = 20
+
 
 class Predictor(DefaultPredictor):
     def __init__(self, cfg):
@@ -102,3 +104,8 @@ def export_csv(self, dest_path=None):
                 class_name = MAP_NAMES[class_]
                 quantities.loc[filename, class_name] += 1
         quantities.to_csv(dest_path, sep=';')
+
+
+def adjust_zoom(cfg, target_zoom):
+    cfg.INPUT.MIN_SIZE_TEST *= DEFAULT_ZOOM / target_zoom
+    cfg.INPUT.MAX_SIZE_TEST *= DEFAULT_ZOOM / target_zoom