from PIL import Image
num_classes = 80
input_size = 416
graph = tf.Graph()
image_path = "./docs/road.jpeg"
original_image = cv2.imread(image_path)
original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)
original_image_size = original_image.shape[:2]
image_data = utils.image_preporcess(np.copy(original_image), [input_size, input_size])
image_data = image_data[np.newaxis, ...]
image_data = image_data.astype(np.float32)
input_data = tf.keras.layers.Input([416, 416, 3])
model = yolov3.YOLOV3(input_data).model
utils.load_weights(model, "./yolov3.weights")
pred_sbbox, pred_mbbox, pred_lbbox = model(image_data)
pred_bbox = np.concatenate([np.reshape(pred_sbbox, (-1, 5 + num_classes)),
np.reshape(pred_mbbox, (-1, 5 + num_classes)),
np.reshape(pred_lbbox, (-1, 5 + num_classes))], axis=0)
bboxes = utils.postprocess_boxes(pred_bbox, original_image_size, input_size, 0.3)
bboxes = utils.nms(bboxes, 0.45, method='nms')
image = utils.draw_bbox(original_image, bboxes)
image = Image.fromarray(image)
image.show()
import core.yolov3 as yolov3
from PIL import Image
num_classes = 80
input_size = 416
graph = tf.Graph()
image_path = "./docs/kite.jpg"
original_image = cv2.imread(image_path)
original_image = cv2.cvtColor(original_image, cv2.COLOR_BGR2RGB)
original_image_size = original_image.shape[:2]
image_data = utils.image_preporcess(np.copy(original_image), [input_size, input_size])
image_data = image_data[np.newaxis, ...].astype(np.float32)
input_layer = tf.keras.layers.Input([input_size, input_size, 3])
model = yolov3.YOLOV3(input_layer)
model.load_weights("./yolov3.weights")
# model = model.model
# model.load_weights("./yolov3")
# pred_sbbox, pred_mbbox, pred_lbbox = model(image_data)
pred_sbbox, pred_mbbox, pred_lbbox = model.inference(image_data)
pred_bbox = np.concatenate([np.reshape(pred_sbbox, (-1, 5 + num_classes)),
np.reshape(pred_mbbox, (-1, 5 + num_classes)),
np.reshape(pred_lbbox, (-1, 5 + num_classes))], axis=0)
bboxes = utils.postprocess_boxes(pred_bbox, original_image_size, input_size, 0.3)
bboxes = utils.nms(bboxes, 0.45, method='nms')
image = utils.draw_bbox(original_image, bboxes)
image = Image.fromarray(image)
image.show()