8a5a6993cec37c98e823d251febcd0b91089bd44,keract/keract.py,,display_heatmaps,#Any#Any#Any#,88

Before Change

            continue
        print("")
        fig = plt.figure(figsize=(12, 12))
        plt.axis("off")
        plt.title(layer_name)
        // computes values required to scale the activations (which will form our heat map) to be in range 0-1
        scaler = MinMaxScaler()
        scaler.fit(acts.reshape(-1, 1))

After Change

        scaler = MinMaxScaler()
        scaler.fit(acts.reshape(-1, 1))
        for i in range(nrows * ncols):
            if i < acts.shape[-1]:
                img = acts[0, :, :, i]
                // scale the activations (which will form our heat map) to be in range 0-1
                img = scaler.transform(img)
                // resize heatmap to be same dimensions of image
                img = Image.fromarray(img)
                img = img.resize((image.shape[0], image.shape[1]), Image.BILINEAR)
                img = np.array(img)
                axes.flat[i].imshow(img / 255.0)
                // overlay a 70% transparent heat map onto the image
                // Lowest activations are dark, highest are dark red, mid are yellow
                axes.flat[i].imshow(img, alpha=0.3, cmap="jet", interpolation="bilinear")
            axes.flat[i].axis("off")
        if save:
            plt.savefig(layer_name.split("/")[0] + ".png", bbox_inches="tight")
        else:

Instances