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import imutils |
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import pickle |
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from tensorflow.keras.models import load_model |
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def buka(title, image): |
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image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB) |
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plt.imshow(image) |
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plt.title(title) |
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plt.grid(False) |
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plt.axis("off") |
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plt.show() |
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print("loading model....") |
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model = load_model('/content/bananafreshness/pisang.model') |
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mlb = pickle.loads(open('/content/bananafreshness/pisang.pickle', "rb").read()) |
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image = cv2.imread("/content/pisang-busuk-sebagian_20171004_085005.jpg") |
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output = imutils.resize(image, width=400) |
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image = cv2.resize(image, (94, 94)) |
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image = image.astype("float") / 255.0 |
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image = img_to_array(image) |
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image = np.expand_dims(image, axis=0) |
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proba = model.predict(image)[0] |
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idxs = np.argsort(proba)[::-1][:2] |
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for (i, j) in enumerate(idxs): |
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label = "{}: {:.2f}%".format(mlb.classes_[j], proba[j] * 100) |
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cv2.putText(output, label, (10, (i * 30) + 25), |
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cv2.FONT_HERSHEY_SIMPLEX, 0.7, (0, 255, 0), 2) |
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for (label, p) in zip(mlb.classes_, proba): |
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print("{}: {:.2f}%".format(label, p * 100)) |
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buka("Output", output) |
