X-Git-Url: https://gerrit.akraino.org/r/gitweb?a=blobdiff_plain;f=example-apps%2FPDD%2Fpcb-defect-detection%2Fdata%2Flib_coco%2Fget_coco_next_batch.py;fp=example-apps%2FPDD%2Fpcb-defect-detection%2Fdata%2Flib_coco%2Fget_coco_next_batch.py;h=ec56b1a12cbfa428ac421b4b6bc47cebe33a0785;hb=a785567fb9acfc68536767d20f60ba917ae85aa1;hp=0000000000000000000000000000000000000000;hpb=94a133e696b9b2a7f73544462c2714986fa7ab4a;p=ealt-edge.git

diff --git a/example-apps/PDD/pcb-defect-detection/data/lib_coco/get_coco_next_batch.py b/example-apps/PDD/pcb-defect-detection/data/lib_coco/get_coco_next_batch.py
new file mode 100755
index 0000000..ec56b1a
--- /dev/null
+++ b/example-apps/PDD/pcb-defect-detection/data/lib_coco/get_coco_next_batch.py
@@ -0,0 +1,73 @@
+# -*- coding: utf-8 -*-
+
+from __future__ import absolute_import, print_function, division
+
+import sys, os
+# sys.path.insert(0, os.path.abspath('.'))
+sys.path.insert(0, './PythonAPI/')
+# sys.path.insert(0, os.path.abspath('data'))
+for _ in sys.path:
+    print (_)
+from PythonAPI.pycocotools.coco import COCO
+import cv2
+import numpy as np
+import os
+from libs.label_name_dict import coco_dict
+
+
+annotation_path = '/home/yjr/DataSet/COCO/2017/annotations/instances_train2017.json'
+print ("load coco .... it will cost about 17s..")
+coco = COCO(annotation_path)
+
+imgId_list = coco.getImgIds()
+imgId_list = np.array(imgId_list)
+
+total_imgs = len(imgId_list)
+
+# print (NAME_LABEL_DICT)
+
+
+def next_img(step):
+
+    if step % total_imgs == 0:
+        np.random.shuffle(imgId_list)
+    imgid = imgId_list[step % total_imgs]
+
+    imgname = coco.loadImgs(ids=[imgid])[0]['file_name']
+    # print (type(imgname), imgname)
+    img = cv2.imread(os.path.join("/home/yjr/DataSet/COCO/2017/train2017", imgname))
+
+    annotation = coco.imgToAnns[imgid]
+    gtbox_and_label_list = []
+    for ann in annotation:
+        box = ann['bbox']
+
+        box = [box[0], box[1], box[0]+box[2], box[1]+box[3]]  # [xmin, ymin, xmax, ymax]
+        cat_id = ann['category_id']
+        cat_name = coco_dict.originID_classes[cat_id] #ID_NAME_DICT[cat_id]
+        label = coco_dict.NAME_LABEL_MAP[cat_name]
+        gtbox_and_label_list.append(box + [label])
+    gtbox_and_label_list = np.array(gtbox_and_label_list, dtype=np.int32)
+    # print (img.shape, gtbox_and_label_list.shape)
+    if gtbox_and_label_list.shape[0] == 0:
+        return next_img(step+1)
+    else:
+        return imgid, img[:, :, ::-1], gtbox_and_label_list
+
+
+if __name__ == '__main__':
+
+    imgid, img,  gtbox = next_img(3234)
+
+    print("::")
+    from libs.box_utils.draw_box_in_img import draw_boxes_with_label_and_scores
+
+    img = draw_boxes_with_label_and_scores(img_array=img, boxes=gtbox[:, :-1], labels=gtbox[:, -1],
+                                           scores=np.ones(shape=(len(gtbox), )))
+    print ("_----")
+
+
+    cv2.imshow("test", img)
+    cv2.waitKey(0)
+
+