From 5b3bd6d96aa923b3dc4ec306b8f1b3069e4e5bc5 Mon Sep 17 00:00:00 2001
From: rick <31221441+rwarren2163@users.noreply.github.com>
Date: Mon, 18 May 2020 11:39:41 -0400
Subject: [PATCH] Prevent connecting un-labelled features

Here's a simple fix preventing edges from being drawn to connect a feature with another un-labelled feature, which will have coordinates of [-999999 -999999]
---
 deepposekit/utils/keypoints.py | 27 ++++++++++++++-------------
 1 file changed, 14 insertions(+), 13 deletions(-)

diff --git a/deepposekit/utils/keypoints.py b/deepposekit/utils/keypoints.py
index cb89186..0d8b61f 100644
--- a/deepposekit/utils/keypoints.py
+++ b/deepposekit/utils/keypoints.py
@@ -73,19 +73,20 @@ def draw_graph(keypoints, height, width, output_shape, graph, sigma=1, linewidth
             if line >= 0:
                 pt1 = keypoints[line_idx]
                 pt2 = keypoints[line]
-                line_map = cv2.line(
-                    zeros.copy(),
-                    (int(pt1[0]), int(pt1[1])),
-                    (int(pt2[0]), int(pt2[1])),
-                    1,
-                    linewidth,
-                    lineType=cv2.LINE_AA,
-                )
-                blurred = cv2.GaussianBlur(
-                    line_map.astype(np.float64), (height + 1, width + 1), sigma
-                )
-                resized = cv2.resize(blurred, (out_width, out_height)) + MACHINE_EPSILON
-                edge_confidence[..., jdx] = resized
+                if np.all(pt1>=0) and np.all(pt2>=0):  # make sure we don't draw edge for features that are not labelled within the frame
+                    line_map = cv2.line(
+                        zeros.copy(),
+                        (int(pt1[0]), int(pt1[1])),
+                        (int(pt2[0]), int(pt2[1])),
+                        1,
+                        linewidth,
+                        lineType=cv2.LINE_AA,
+                    )
+                    blurred = cv2.GaussianBlur(
+                        line_map.astype(np.float64), (height + 1, width + 1), sigma
+                    )
+                    resized = cv2.resize(blurred, (out_width, out_height)) + MACHINE_EPSILON
+                    edge_confidence[..., jdx] = resized
         edge_confidence = edge_confidence[..., 1:]
         edge_confidence_list.append(edge_confidence)
         confidence[..., idx] = edge_confidence.sum(-1)