Update OTX explain CLI arguments (#2671)

* Change int8 to uint8 to XAI tests

* Add probabilities for CLI demo

* Rename arguments for explain

* Fix pre-commit

* Remove extra changes

* Fix integration tests

* Fix integration "explain_all_classes" test for OV

docs/source/guide/get_started/cli_commands.rst

@@ -449,7 +449,7 @@ With the ``--help`` command, you can list additional information, such as its pa
 .. code-block::
 
     (otx) ...$ otx explain --help
-    usage: otx explain [-h] --explain-data-roots EXPLAIN_DATA_ROOTS [--save-explanation-to SAVE_EXPLANATION] --load-weights LOAD_WEIGHTS [--explain-algorithm EXPLAIN_ALGORITHM] [--overlay-weight OVERLAY_WEIGHT] [template] {params} ...
+    usage: otx explain [-h] --input INPUT [--output OUTPUT] --load-weights LOAD_WEIGHTS [--explain-algorithm EXPLAIN_ALGORITHM] [--overlay-weight OVERLAY_WEIGHT] [template] {params} ...
 
     positional arguments:
       template              Enter the path or ID or name of the template file.
@@ -459,9 +459,9 @@ With the ``--help`` command, you can list additional information, such as its pa
 
     optional arguments:
       -h, --help            show this help message and exit
-      --explain-data-roots EXPLAIN_DATA_ROOTS
+      -i INPUT, --input INPUT
                             Comma-separated paths to explain data folders.
-      --save-explanation-to SAVE_EXPLANATION_TO
+      -o OUTPUT, --output OUTPUT
                             Output path for explanation images.
       --load-weights LOAD_WEIGHTS
                             Load model weights from previously saved checkpoint.
@@ -475,13 +475,13 @@ With the ``--help`` command, you can list additional information, such as its pa
                             Weight of the saliency map when overlaying the input image with saliency map.
 
 
-The command below will generate saliency maps (heatmaps with red colored areas of focus) of the trained model on the provided dataset and save the resulting images to ``save-explanation-to`` path:
+The command below will generate saliency maps (heatmaps with red colored areas of focus) of the trained model on the provided dataset and save the resulting images to ``output`` path:
 
 .. code-block::
 
-    (otx) ...$ otx explain SSD --explain-data-roots <path/to/explain/root> \
+    (otx) ...$ otx explain SSD --input <path/to/explain/root> \
                                --load-weights <path/to/model_weights> \
-                               --save-explanation-to <path/to/output/root> \
+                               --output <path/to/output/root> \
                                --explain-algorithm classwisesaliencymap \
                                --overlay-weight 0.5
 
@@ -496,9 +496,9 @@ By default, the model is exported to the OpenVINO™ IR format without extra fea
     (otx) ...$ otx export SSD --load-weights <path/to/trained/weights.pth> \
                               --output outputs/openvino/with_features \
                               --dump-features
-    (otx) ...$ otx explain SSD --explain-data-roots <path/to/explain/root> \
+    (otx) ...$ otx explain SSD --input <path/to/explain/root> \
                                --load-weights outputs/openvino/with_features \
-                               --save-explanation-to <path/to/output/root> \
+                               --output <path/to/output/root> \
                                --explain-algorithm classwisesaliencymap \
                                --overlay-weight 0.5
 

docs/source/guide/tutorials/base/explain.rst

@@ -22,12 +22,12 @@ created in the previous step.
   . venv/otx/bin/activate
 
 2. ``otx explain`` returns saliency maps (heatmaps with red colored areas of focus) 
-at the path specified by ``--save-explanation-to``.
+at the path specified by ``--output``.
 
 .. code-block::
 
-    otx explain --explain-data-roots otx-workspace-DETECTION/splitted_dataset/val/ \
-                --save-explanation-to outputs/explanation \
+    otx explain --input otx-workspace-DETECTION/splitted_dataset/val/ \
+                --output outputs/explanation \
                 --load-weights outputs/weights.pth
 
 3. To specify the algorithm of saliency map creation for classification, 
@@ -48,7 +48,7 @@ For detection task, we can choose between the following methods:
 
 
 4. As a result we will get a folder with a pair of generated 
-images for each image in ``--explain-data-roots``: 
+images for each image in ``--input``: 
 
 - saliency map - where red color means more attention of the model
 - overlay - where the saliency map is combined with the original image:

src/otx/cli/tools/explain.py

@@ -50,12 +50,14 @@ def get_args():
     parser, hyper_parameters, params = get_parser_and_hprams_data()
 
     parser.add_argument(
-        "--explain-data-roots",
+        "-i",
+        "--input",
         required=True,
         help="Comma-separated paths to explain data folders.",
     )
     parser.add_argument(
-        "--save-explanation-to",
+        "-o",
+        "--output",
         default="saliency_dump",
         help="Output path for explanation images.",
     )
@@ -123,10 +125,7 @@ def _log_after_saving(explain_predicted_classes, explained_image_counter, args,
             "Please adjust training pipeline or use different model-data pair."
         )
     if explained_image_counter > 0:
-        logger.info(
-            f"Saliency maps saved to {args.save_explanation_to} for {explained_image_counter} "
-            f"out of {num_images} images."
-        )
+        logger.info(f"Saliency maps saved to {args.output} for {explained_image_counter} out of {num_images} images.")
 
 
 def main():
@@ -169,10 +168,10 @@ def main():
             f"{args.explain_algorithm} currently not supported. \
             Currently only support {SUPPORTED_EXPLAIN_ALGORITHMS}"
         )
-    if not Path(args.save_explanation_to).exists():
-        Path(args.save_explanation_to).mkdir(parents=True)
+    if not Path(args.output).exists():
+        Path(args.output).mkdir(parents=True)
 
-    image_files = get_image_files(args.explain_data_roots)
+    image_files = get_image_files(args.input)
     dataset_to_explain = get_explain_dataset_from_filelist(image_files)
     explain_predicted_classes = not args.explain_all_classes
     explain_parameters = ExplainParameters(
@@ -201,7 +200,7 @@ def main():
                 process_saliency_maps=explain_parameters.process_saliency_maps,
                 img=explained_data.numpy,
                 saliency_map=saliency_data.numpy,
-                save_dir=args.save_explanation_to,
+                save_dir=args.output,
                 fname=fname,
                 weight=args.overlay_weight,
             )

src/otx/cli/tools/utils/demo/visualization.py

@@ -71,7 +71,7 @@ def draw_masks(frame: Mat, predictions, put_object_count: bool = False):
         cv2.drawContours(frame, contours, -1, color, 1)
         rect = cv2.boundingRect(contours[0])
         cv2.rectangle(frame, (rect[0], rect[1]), (rect[0] + rect[2], rect[1] + rect[3]), color, 1)
-        put_text_on_rect_bg(frame, label.name, (rect[0], rect[1]), color=color)
+        put_text_on_rect_bg(frame, f"{label.name} {label.probability*100:.1f}%", (rect[0], rect[1]), color=color)
         cv2.bitwise_or(aggregated_mask, mask, dst=aggregated_mask)
         cv2.bitwise_or(
             aggregated_colored_mask,
@@ -110,7 +110,7 @@ def put_labels(frame: Mat, predictions: List[Annotation]):
     assert len(predictions[0].get_labels()) == 1
     label = predictions[0].get_labels()[0]
     color = tuple(getattr(label.color, x) for x in ("blue", "green", "red"))
-    put_text_on_rect_bg(frame, label.name, (0, 0), color=color)
+    put_text_on_rect_bg(frame, f"{label.name} {label.probability*100:.1f}%", (0, 0), color=color)
     return frame
 
 
@@ -129,7 +129,7 @@ def draw_bounding_boxes(frame: Mat, predictions: List[Annotation], put_object_co
             label = prediction.get_labels()[0]
             color = tuple(getattr(label.color, x) for x in ("blue", "green", "red"))
             cv2.rectangle(frame, (x1, y1), (x2, y2), color, thickness=2)
-            put_text_on_rect_bg(frame, label.name, (x1, y1), color=color)
+            put_text_on_rect_bg(frame, f"{label.name} {label.probability*100:.1f}%", (x1, y1), color=color)
         else:
             warn(
                 f"Predictions called on Annotations with shape {type(prediction.shape)}."

tests/test_suite/run_test_command.py

@@ -859,16 +859,16 @@ def otx_explain_testing(template, root, otx_dir, args, trained=False):
 
     save_dir = f"explain_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,
@@ -899,16 +899,16 @@ def otx_explain_testing_all_classes(template, root, otx_dir, args):
 
     save_dir = f"explain_all_classes_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,
@@ -923,7 +923,7 @@ def otx_explain_testing_all_classes(template, root, otx_dir, args):
         assert len(os.listdir(output_dir)) == len(os.listdir(output_dir_explain_only_predicted_classes))
     else:
         assert len(os.listdir(output_dir)) >= len(os.listdir(output_dir_explain_only_predicted_classes))
-    assert all([os.path.splitext(fname)[1] == ".tiff" for fname in os.listdir(output_dir)])
+    assert all([os.path.splitext(fname)[1] in [".tiff", ".log"] for fname in os.listdir(output_dir)])
 
 
 def otx_explain_testing_process_saliency_maps(template, root, otx_dir, args, trained=False):
@@ -945,16 +945,16 @@ def otx_explain_testing_process_saliency_maps(template, root, otx_dir, args, tra
 
     save_dir = f"explain_process_saliency_maps_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,
@@ -986,16 +986,16 @@ def otx_explain_openvino_testing(template, root, otx_dir, args, trained=False):
 
     save_dir = f"explain_ov_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,
@@ -1027,16 +1027,16 @@ def otx_explain_all_classes_openvino_testing(template, root, otx_dir, args):
 
     save_dir = f"explain_ov_all_classes_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,
@@ -1052,7 +1052,7 @@ def otx_explain_all_classes_openvino_testing(template, root, otx_dir, args):
         assert len(os.listdir(output_dir)) == len(os.listdir(output_dir_explain_only_predicted_classes))
     else:
         assert len(os.listdir(output_dir)) >= len(os.listdir(output_dir_explain_only_predicted_classes))
-    assert all([os.path.splitext(fname)[1] == ".tiff" for fname in os.listdir(output_dir)])
+    assert all([os.path.splitext(fname)[1] in [".tiff", ".log"] for fname in os.listdir(output_dir)])
 
 
 def otx_explain_process_saliency_maps_openvino_testing(template, root, otx_dir, args, trained=False):
@@ -1074,16 +1074,16 @@ def otx_explain_process_saliency_maps_openvino_testing(template, root, otx_dir,
 
     save_dir = f"explain_ov_process_saliency_maps_{template.model_template_id}/{test_algorithm}/{train_type}/"
     output_dir = os.path.join(template_work_dir, save_dir)
-    explain_data_root = os.path.join(otx_dir, args["--input"])
+    data_input = os.path.join(otx_dir, args["--input"])
     command_line = [
         "otx",
         "explain",
         template.model_template_path,
         "--load-weights",
         weights_path,
-        "--explain-data-root",
-        explain_data_root,
-        "--save-explanation-to",
+        "--input",
+        data_input,
+        "--output",
         output_dir,
         "--explain-algorithm",
         test_algorithm,