#!/usr/bin/python3
# Copyright 2017, Mengxiao Lin <linmx0130@gmail.com>
import mxnet as mx
import numpy as np
import cv2
from .nms import nms
from .config import cfg
def show_anchors(data, label, anchors, anchors_chosen, count=None):
"""
show image, ground truth and anchors in the same window
"""
data = data[0].as_in_context(mx.cpu(0))
data[0] = data[0] * 0.229 + 0.485
data[1] = data[1] * 0.224 + 0.456
data[2] = data[2] * 0.225 + 0.406
label = label[0].asnumpy()
img = data.asnumpy()
img = np.array(np.round(img * 255), dtype=np.uint8)
img = np.transpose(img, (1, 2, 0))
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
for item in label:
cv2.rectangle(img, (int(item[0]), int(item[1])), (int(item[2]), int(item[3])), color=(255, 0, 0), thickness=2)
#cv2.putText(img, ds.voc_class_name[int(item[4])], (int(item[0]), int(item[3])),0, 0.5,(0, 255, 0))
anchors = anchors[0].asnumpy()
anchors_chosen = anchors_chosen[0].asnumpy()
anchors = anchors.reshape((-1, 4))
anchors_chosen = anchors_chosen.reshape((-1,))
for anchor_id, c in enumerate(anchors_chosen):
if c==1:
anc = anchors[anchor_id]
cv2.rectangle(img, (int(anc[0]), int(anc[1])), (int(anc[2]), int(anc[3])), color=(0,0, 255), thickness=1)
print((int(anc[0]), int(anc[1])), (int(anc[2]), int(anc[3])))
if count is not None:
count = count - 1
if count == 0:
break
cv2.imshow("Img", img)
cv2.waitKey(0)
def show_detection_result(data, label, bboxes, cls_scores, class_name_list):
data = data[0].as_in_context(mx.cpu(0))
data[0] = data[0] * 0.229 + 0.485
data[1] = data[1] * 0.224 + 0.456
data[2] = data[2] * 0.225 + 0.406
label = label[0].asnumpy()
img = data.asnumpy()
img = np.array(np.round(img * 255), dtype=np.uint8)
img = np.transpose(img, (1, 2, 0))
img = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
bboxes = bboxes.asnumpy()
cls_scores = cls_scores.asnumpy()
# Show ground truth
for item in label:
cv2.rectangle(img, (int(item[0]), int(item[1])), (int(item[2]), int(item[3])), color=(255, 0, 0), thickness=2)
cv2.putText(img, class_name_list[int(item[4])], (int(item[0]), int(item[3])),0, 0.5,(0, 255, 0))
# NMS by class
for cls_id in range(1, len(class_name_list)):
cur_scores = cls_scores[:, cls_id]
bboxes_pick = bboxes[:, cls_id * 4: (cls_id+1)*4]
cur_scores, bboxes_pick = nms(cur_scores, bboxes_pick, cfg.rcnn_nms_thresh)
for i in range(len(cur_scores)):
if cur_scores[i] >= cfg.rcnn_score_thresh:
bbox = bboxes_pick[i]
cv2.rectangle(img, (int(bbox[0]), int(bbox[1])), (int(bbox[2]), int(bbox[3])), color=(0, 0, 255), thickness=1)
cv2.putText(img, "{}: {:.4}".format(class_name_list[cls_id], cur_scores[i]), (int(bbox[0]), int(bbox[3])),0, 0.5,(255, 255, 0))
try:
cv2.imshow("Img", img)
cv2.waitKey(0)
except cv2.error:
cv2.imwrite("det_result.jpg", img)
print("imshow() is not supported! Saved result to det_result.jpg.")
input()
