Exemplo n.º 1
0
def run():
    input_api = InputQueue()

    base_path = os.path.abspath(
        __file__ + "/../../../test/zoo/resources/serving_quick_start")

    if not base_path:
        raise EOFError("You have to set your image path")
    output_api = OutputQueue()
    output_api.dequeue()
    path = os.listdir(base_path)
    for p in path:
        if not p.endswith("jpeg"):
            continue
        img = cv2.imread(os.path.join(base_path, p))
        img = cv2.resize(img, (224, 224))
        input_api.enqueue_image(p, img)

    time.sleep(5)

    # get all result and dequeue
    result = output_api.dequeue()
    for k in result.keys():
        output = "image: " + k + ", classification-result:"
        tmp_dict = json.loads(result[k])
        for class_idx in tmp_dict.keys():
            output += "class: " + class_idx + "'s prob: " + tmp_dict[class_idx]
        print(output)
Exemplo n.º 2
0
def run(path):
    input_api = InputQueue()
    base_path = path

    if not base_path:
        raise EOFError("You have to set your image path")
    output_api = OutputQueue()
    output_api.dequeue()
    path = os.listdir(base_path)
    for p in path:
        if not p.endswith("jpeg"):
            continue
        img = cv2.imread(os.path.join(base_path, p))
        img = cv2.resize(img, (224, 224))
        input_api.enqueue_image(p, img)

    time.sleep(10)

    # get all result and dequeue
    result = output_api.dequeue()
    for k in result.keys():
        output = "image: " + k + ", classification-result:"
        tmp_list = json.loads(result[k])
        for record in range(len(tmp_list)):
            output += " class: " + str(tmp_list[record][0]) \
                      + "'s prob: " + str(tmp_list[record][1])
        print(output)
Exemplo n.º 3
0
import time


if __name__ == "__main__":
    input_api = InputQueue()

    base_path = "../../test/zoo/resources/serving_quick_start"

    if not base_path:
        raise EOFError("You have to set your image path")
    output_api = OutputQueue()
    output_api.dequeue()
    path = os.listdir(base_path)
    for p in path:
        if not p.endswith("jpeg"):
            continue
        img = cv2.imread(os.path.join(base_path, p))
        img = cv2.resize(img, (224, 224))
        input_api.enqueue_image(p, img)

    time.sleep(5)

    # get all result and dequeue
    result = output_api.dequeue()
    for k in result.keys():
        output = "image: " + k + ", classification-result:"
        tmp_dict = json.loads(result[k])
        for class_idx in tmp_dict.keys():
            output += "class: " + class_idx + "'s prob: " + tmp_dict[class_idx]
        print(output)