Correctly detect number of results colors (#789)

We were checking results_color, which will typically be a length 3 list.
This would cause incorrect behavior in the presence of multiple labels.
This switches to always creating results_color_sv upfront and checking
it.

Also adds some type/value checks to the input.

deepforest/visualize.py

@@ -376,7 +376,7 @@ def plot_results(results,
         savedir: optional path to save the figure. If None (default), the figure will be interactively plotted.
         height: height of the image in pixels. Required if the geometry type is 'polygon'.
         width: width of the image in pixels. Required if the geometry type is 'polygon'.
-        results_color (list): color of the results annotations as a tuple of RGB color, e.g. orange annotations is [245, 135, 66]
+        results_color (list or sv.ColorPalette): color of the results annotations as a tuple of RGB color (if a single color), e.g. orange annotations is [245, 135, 66], or an supervision.ColorPalette if multiple labels and specifying colors for each label
         ground_truth_color (list): color of the ground truth annotations as a tuple of RGB color, e.g. blue annotations is [0, 165, 255]
         thickness: thickness of the rectangle border line in px
         basename: optional basename for the saved figure. If None (default), the basename will be extracted from the image path.
@@ -385,17 +385,30 @@ def plot_results(results,
         None
     """
     # Convert colors, check for multi-class labels
-    results_color_sv = sv.Color(results_color[0], results_color[1], results_color[2])
+    if isinstance(results_color, list) and len(results_color) == 3:
+        results_color_sv = sv.Color(results_color[0], results_color[1], results_color[2])
+    elif isinstance(results_color, sv.draw.color.ColorPalette):
+        results_color_sv = results_color
+    elif isinstance(results_color, list):
+        raise ValueError(
+            "results_color must be either a 3 item list containing RGB values or an sv.ColorPalette instance"
+        )
+    else:
+        raise TypeError(
+            "results_color must be either a list of RGB values or an sv.ColorPalette instance"
+        )
+
     ground_truth_color_sv = sv.Color(ground_truth_color[0], ground_truth_color[1],
                                      ground_truth_color[2])
 
     num_labels = len(results.label.unique())
-    if num_labels > 1 and len(results_color) != num_labels:
+    if num_labels > 1 and len(results_color_sv) != num_labels:
         warnings.warn(
-            "Multiple labels detected in the results. Each label will be plotted with a different color using a color ramp, results color argument is ignored."
+            """Multiple labels detected in the results and results_color argument provides a single color.
+            Each label will be plotted with a different color using a built-in color ramp.
+            If you want to customize colors with multiple labels pass a supervision.ColorPalette object to results_color with the appropriate number of labels"""
         )
-        if num_labels > 1:
-            results_color_sv = sv.ColorPalette.from_matplotlib('viridis', num_labels)
+        results_color_sv = sv.ColorPalette.from_matplotlib('viridis', num_labels)
 
     # Read images
     root_dir = results.root_dir