pcb defect detetcion application

[ealt-edge.git] / example-apps / PDD / pcb-defect-detection / libs / box_utils / show_box_in_tensor.py

diff --git a/example-apps/PDD/pcb-defect-detection/libs/box_utils/show_box_in_tensor.py b/example-apps/PDD/pcb-defect-detection/libs/box_utils/show_box_in_tensor.py
new file mode 100755 (executable)
index 0000000..37afda0
--- /dev/null
+++ b/example-apps/PDD/pcb-defect-detection/libs/box_utils/show_box_in_tensor.py
@@ -0,0 +1,70 @@
+# -*- coding: utf-8 -*-
+
+from __future__ import absolute_import
+from __future__ import division
+from __future__ import print_function
+
+import tensorflow as tf
+import numpy as np
+import cv2
+from libs.label_name_dict.label_dict import LABEl_NAME_MAP
+
+from libs.configs import cfgs
+
+from libs.box_utils import draw_box_in_img
+
+def only_draw_boxes(img_batch, boxes):
+
+    boxes = tf.stop_gradient(boxes)
+    img_tensor = tf.squeeze(img_batch, 0)
+    img_tensor = tf.cast(img_tensor, tf.float32)
+    labels = tf.ones(shape=(tf.shape(boxes)[0], ), dtype=tf.int32) * draw_box_in_img.ONLY_DRAW_BOXES
+    scores = tf.zeros_like(labels, dtype=tf.float32)
+    img_tensor_with_boxes = tf.py_func(draw_box_in_img.draw_boxes_with_label_and_scores,
+                                       inp=[img_tensor, boxes, labels, scores],
+                                       Tout=tf.uint8)
+    img_tensor_with_boxes = tf.reshape(img_tensor_with_boxes, tf.shape(img_batch))  # [batch_size, h, w, c]
+
+    return img_tensor_with_boxes
+
+def draw_boxes_with_scores(img_batch, boxes, scores):
+
+    boxes = tf.stop_gradient(boxes)
+    scores = tf.stop_gradient(scores)
+
+    img_tensor = tf.squeeze(img_batch, 0)
+    img_tensor = tf.cast(img_tensor, tf.float32)
+    labels = tf.ones(shape=(tf.shape(boxes)[0],), dtype=tf.int32) * draw_box_in_img.ONLY_DRAW_BOXES_WITH_SCORES
+    img_tensor_with_boxes = tf.py_func(draw_box_in_img.draw_boxes_with_label_and_scores,
+                                       inp=[img_tensor, boxes, labels, scores],
+                                       Tout=[tf.uint8])
+    img_tensor_with_boxes = tf.reshape(img_tensor_with_boxes, tf.shape(img_batch))
+    return img_tensor_with_boxes
+
+def draw_boxes_with_categories(img_batch, boxes, labels):
+    boxes = tf.stop_gradient(boxes)
+
+    img_tensor = tf.squeeze(img_batch, 0)
+    img_tensor = tf.cast(img_tensor, tf.float32)
+    scores = tf.ones(shape=(tf.shape(boxes)[0],), dtype=tf.float32)
+    img_tensor_with_boxes = tf.py_func(draw_box_in_img.draw_boxes_with_label_and_scores,
+                                       inp=[img_tensor, boxes, labels, scores],
+                                       Tout=[tf.uint8])
+    img_tensor_with_boxes = tf.reshape(img_tensor_with_boxes, tf.shape(img_batch))
+    return img_tensor_with_boxes
+
+def draw_boxes_with_categories_and_scores(img_batch, boxes, labels, scores):
+    boxes = tf.stop_gradient(boxes)
+    scores = tf.stop_gradient(scores)
+
+    img_tensor = tf.squeeze(img_batch, 0)
+    img_tensor = tf.cast(img_tensor, tf.float32)
+    img_tensor_with_boxes = tf.py_func(draw_box_in_img.draw_boxes_with_label_and_scores,
+                                       inp=[img_tensor, boxes, labels, scores],
+                                       Tout=[tf.uint8])
+    img_tensor_with_boxes = tf.reshape(img_tensor_with_boxes, tf.shape(img_batch))
+    return img_tensor_with_boxes
+
+if __name__ == "__main__":
+    print (1)
+