From 737c8ccb4fa986de0c4dbee3e74a64b5266ed232 Mon Sep 17 00:00:00 2001
From: Alexander Pacha <alexander.pacha@gmail.com>
Date: Mon, 23 Apr 2018 12:13:17 +0200
Subject: [PATCH] Increasing the default number of detections and boxes to draw
 from 20 to 1200 for dense scores

---
 research/object_detection/eval_util.py                 | 2 +-
 research/object_detection/model_lib.py                 | 2 +-
 research/object_detection/protos/eval.proto            | 2 +-
 research/object_detection/utils/visualization_utils.py | 6 +++---
 4 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/research/object_detection/eval_util.py b/research/object_detection/eval_util.py
index 89ebd6cb79b..5ba3e09b9be 100644
--- a/research/object_detection/eval_util.py
+++ b/research/object_detection/eval_util.py
@@ -68,7 +68,7 @@ def visualize_detection_results(result_dict,
                                 show_groundtruth=False,
                                 groundtruth_box_visualization_color='black',
                                 min_score_thresh=.5,
-                                max_num_predictions=20,
+                                max_num_predictions=1200,
                                 skip_scores=False,
                                 skip_labels=False,
                                 keep_image_id_for_visualization_export=False):
diff --git a/research/object_detection/model_lib.py b/research/object_detection/model_lib.py
index 1a4bc844da7..1f48bef0392 100644
--- a/research/object_detection/model_lib.py
+++ b/research/object_detection/model_lib.py
@@ -350,7 +350,7 @@ def tpu_scaffold():
       if not use_tpu and use_original_images:
         detection_and_groundtruth = (
             vis_utils.draw_side_by_side_evaluation_image(
-                eval_dict, category_index, max_boxes_to_draw=20,
+                eval_dict, category_index, max_boxes_to_draw=1200,
                 min_score_thresh=0.2))
         img_summary = tf.summary.image('Detections_Left_Groundtruth_Right',
                                        detection_and_groundtruth)
diff --git a/research/object_detection/protos/eval.proto b/research/object_detection/protos/eval.proto
index f216c91a9ab..35c33a3c969 100644
--- a/research/object_detection/protos/eval.proto
+++ b/research/object_detection/protos/eval.proto
@@ -50,7 +50,7 @@ message EvalConfig {
   optional float min_score_threshold = 13 [default=0.5];
 
   // Maximum number of detections to visualize
-  optional int32 max_num_boxes_to_visualize = 14 [default=20];
+  optional int32 max_num_boxes_to_visualize = 14 [default=1200];
 
   // When drawing a single detection, each label is by default visualized as
   // <label name> : <label score>. One can skip the name or/and score using the
diff --git a/research/object_detection/utils/visualization_utils.py b/research/object_detection/utils/visualization_utils.py
index 6cfa63aecbb..82e7a6afa15 100644
--- a/research/object_detection/utils/visualization_utils.py
+++ b/research/object_detection/utils/visualization_utils.py
@@ -314,7 +314,7 @@ def draw_bounding_boxes_on_image_tensors(images,
                                          category_index,
                                          instance_masks=None,
                                          keypoints=None,
-                                         max_boxes_to_draw=20,
+                                         max_boxes_to_draw=1200,
                                          min_score_thresh=0.2):
   """Draws bounding boxes, masks, and keypoints on batch of image tensors.
 
@@ -381,7 +381,7 @@ def draw_boxes(image_and_detections):
 
 def draw_side_by_side_evaluation_image(eval_dict,
                                        category_index,
-                                       max_boxes_to_draw=20,
+                                       max_boxes_to_draw=1200,
                                        min_score_thresh=0.2):
   """Creates a side-by-side image with detections and groundtruth.
 
@@ -535,7 +535,7 @@ def visualize_boxes_and_labels_on_image_array(
     instance_boundaries=None,
     keypoints=None,
     use_normalized_coordinates=False,
-    max_boxes_to_draw=20,
+    max_boxes_to_draw=1200,
     min_score_thresh=.5,
     agnostic_mode=False,
     line_thickness=4,