[FIXED] numpy.ndarray object has no attribute 'read'(and 'seek')

Issue

I am getting the error numpy.ndarray object has no attribute 'read' and numpy.ndarray object has no attribute 'seek'. I tried looking for the answer online but I failed.

What I am trying to do is detect objects in a video - in this case I want to detect zebras.

I took an image detector and I am trying to apply it to video. I am trying to loop over each frame of the video and ultimately passing the frame to the function draw_boxes.

Here is the error message:

Traceback (most recent call last):
  File "/Users/ysquared/Library/Python/3.7/lib/python/site-packages/PIL/Image.py", line 2770, in open
    fp.seek(0)
AttributeError: 'numpy.ndarray' object has no attribute 'seek'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<string>", line 204, in <module>
  File "<string>", line 118, in load_image_pixels
  File "/Users/ysquared/Library/Python/3.7/lib/python/site-packages/keras_preprocessing/image/utils.py", line 110, in load_img
    img = pil_image.open(path)
  File "/Users/ysquared/Library/Python/3.7/lib/python/site-packages/PIL/Image.py", line 2772, in open
    fp = io.BytesIO(fp.read())
AttributeError: 'numpy.ndarray' object has no attribute 'read'

And here is the relevant code:

model = load_model('model.h5')

# define the expected input shape for the model
input_w, input_h = 416, 416

# define the anchors
anchors = [[116,90, 156,198, 373,326], [30,61, 62,45, 59,119], [10,13, 16,30, 33,23]]

# define the labels
labels = ["person", "bicycle", "car", "motorbike", "aeroplane", "bus", "train", "truck",
        "boat", "traffic light", "fire hydrant", "stop sign", "parking meter", "bench",
        "bird", "cat", "dog", "horse", "sheep", "cow", "elephant", "bear", "zebra", "giraffe",
        "backpack", "umbrella", "handbag", "tie", "suitcase", "frisbee", "skis", "snowboard",
        "sports ball", "kite", "baseball bat", "baseball glove", "skateboard", "surfboard",
        "tennis racket", "bottle", "wine glass", "cup", "fork", "knife", "spoon", "bowl", "banana",
        "apple", "sandwich", "orange", "broccoli", "carrot", "hot dog", "pizza", "donut", "cake",
        "chair", "sofa", "pottedplant", "bed", "diningtable", "toilet", "tvmonitor", "laptop", "mouse",
        "remote", "keyboard", "cell phone", "microwave", "oven", "toaster", "sink", "refrigerator",
        "book", "clock", "vase", "scissors", "teddy bear", "hair drier", "toothbrush"]

vs = cv2.VideoCapture('Zebras.mp4')
fourcc = cv2.VideoWriter_fourcc(*'XVID')
writer = cv2.VideoWriter('output.avi', fourcc, 20.0, (640, 480))

class_threshold = 0.6
boxes = list()

while True:
    (grabbed, frame) = vs.read()

    if grabbed==True:

        image, image_w, image_h = load_image_pixels(frame, (input_w, input_h))
        yhat = model.predict(image)

        for i in range(len(yhat)):
            # decode the output of the network
            boxes += decode_netout(yhat[i][0], anchors[i], class_threshhold, input_h, input_w)
         # correct the sizes of the bounding boxes for the shape of the image
        correct_yolo_boxes(boxes, image_h, image_w, input_h, input_w)
         # suppress non-maximal boxes
        do_nms(boxes, 0.5)

         # get the details of the detected objects
        v_boxes, v_labels, v_scores = get_boxes(boxes, labels, class_threshold)

         # draw what we found
        frame = draw_boxes(frame, v_boxes, v_labels, v_scores)

        writer.write(frame)

        cv2.imshow('frame', frame)

        if cv2.waitkey(1) & 0xFF == ord('q'):
            break

    else:
        break

vs.release()

writer.release()

cv2.destroyAllWindows()

Solution

Here is how I solved the problem(i.e got rid of the error):

##[..] 
cv2.imwrite("framex.jpg", frame)
filename = "framex.jpg"

image, image_w, image_h = load_image_pixels(filename, (input_w, input_h))

##[..]

frame = draw_boxes(filename, v_boxes, v_labels, v_scores)

##[..]

Answered By - ysquared