make the app much faster

app.py

@@ -31,7 +31,7 @@ def image_loading_batch(input: Path, args: argparse.Namespace) -> dict:
         return {"name": input.name, "path": input, "buffer": None}
 
 
-def main(argv):
+def main(argv, low_resource_demo=True):
     batch = Batch(argv)
     batch.set_io_description(
         input_help='input image files',
@@ -40,19 +40,23 @@ def main(argv):
     parser = get_parser()
     parser.add_argument("-nop", "--disable-preload", action="store_true", help="Disable images preload")
     args = batch.parse_args(parser)
-    # batch.set_multiprocessing_enabled(False)
+    backend = args.backend
+    if backend == "qt":
+        batch.set_multiprocessing_enabled(False)
     img_list = batch.run(image_loading_batch)
     if args.keyboard:
         image_control = KeyboardControl(0, [0, len(img_list)-1], keydown="3", keyup="9", modulo=True)
     else:
         image_control = (0, [0, len(img_list)-1])
     interactive(image_index=image_control)(image_selector)
-    plug_crop_selector(num_pad=args.keyboard)
-    # plug_configure_metrics(key_shortcut="a")  # "a" if args.keyboard else None)
-    # plug_morph_canvas()
+    plug_crop_selector(num_pad=args.keyboard, low_resources=low_resource_demo)
+    if not low_resource_demo:
+        plug_configure_metrics(key_shortcut="a")  # "a" if args.keyboard else None)
+    if args.backend != "gradio":
+        plug_morph_canvas()
     model_dict = get_default_models(args.experiments, Path(args.models_storage), keyboard_control=args.keyboard)
     interactive_pipeline(
-        gui=args.backend,
+        gui=backend,
         cache=True,
         safe_input_buffer_deepcopy=False
     )(natural_inference_pipeline)(
@@ -63,4 +67,4 @@ def main(argv):
 
 if __name__ == "__main__":
     # main(sys.argv[1:])
-    main(["-e", "6002", "5002", "-i", "__dataset/sample/*.*g",  "-b", "gradio"])
+    main(["-e", "6002", "5002", "-i", "__dataset/sample/*.*g",  "-b", "gradio"], low_resource_demo=True)

src/rstor/analyzis/interactive/crop.py

@@ -45,11 +45,15 @@ def crop_selector(image, center_x=0.5, center_y=0.5, size=9., global_params={}):
     return
 
 
-def plug_crop_selector(num_pad: bool = False):
+def plug_crop_selector(num_pad: bool = False, low_resources: bool = False):
+    if low_resources:
+        size_control = (5., [5., 7., 0.3], "crop size", ["+", "-"])
+    else:
+        size_control = (9., [6., 13., 0.3], "crop size", ["+", "-"])
     interactive(
         center_x=(0.5, [0., 1.], "cx", ["4" if num_pad else "left", "6" if num_pad else "right"]),
         center_y=(0.5, [0., 1.], "cy", ["8" if num_pad else "up", "2" if num_pad else "down"]),
-        size=(9., [6., 13., 0.3], "crop size", ["+", "-"])
+        size=size_control
     )(crop_selector)
 
 

src/rstor/analyzis/interactive/pipelines.py

@@ -54,8 +54,9 @@ def natural_inference_pipeline(input_image_list: List[np.ndarray], models_dict:
     degraded = degrade_noise(degraded)
     blur_kernel = rescale_thumbnail(blur_kernel)
     restored = infer(degraded, model)
-    configure_metrics()
-    get_metrics_restored(restored, groundtruth)
-    get_metrics_degraded(degraded, groundtruth)
-    morph_canvas()
-    return [[degraded, restored], [blur_kernel, groundtruth]]
+    # configure_metrics()
+    # get_metrics_restored(restored, groundtruth)
+    # get_metrics_degraded(degraded, groundtruth)
+    # morph_canvas()
+    # return [[degraded, restored], [blur_kernel, groundtruth]]
+    return [degraded, restored, groundtruth, blur_kernel]