Update app.py

app.py

@@ -59,46 +59,7 @@ class Explainer:
         fig, _ = viz.visualize_image_attr_multiple(np.transpose(attributions_gs.squeeze().cpu().detach().numpy(), (1,2,0)),
                                             np.transpose(self.transformed_img.squeeze().cpu().detach().numpy(), (1,2,0)),
                                             ["original_image", "heat_map"],
-                                            ["all", "absolute_value"],
-                                            cmap=self.default_cmap,
-                                            show_colorbar=True)
-        fig.suptitle("SHAP | " + self.fig_title, fontsize=12)
-        return self.convert_fig_to_pil(fig)
-
-    def occlusion(self, stride, sliding_window):
-        occlusion = Occlusion(model)
-
-        attributions_occ = occlusion.attribute(self.input,
-                                               target=self.pred_label_idx,
-                                               strides=(3, int(stride), int(stride)),
-                                               sliding_window_shapes=(3, int(sliding_window), int(sliding_window)),
-                                               baselines=0)
-
-        fig, _ = viz.visualize_image_attr_multiple(np.transpose(attributions_occ.squeeze().cpu().detach().numpy(), (1,2,0)),
-                                            np.transpose(self.transformed_img.squeeze().cpu().detach().numpy(), (1,2,0)),
-                                            ["original_image", "heat_map", "heat_map", "masked_image"],
-                                            ["all", "positive", "negative", "positive"],
-                                            show_colorbar=True,
-                                            titles=["Original", "Positive Attribution", "Negative Attribution", "Masked"],
-                                            fig_size=(18, 6)
-                                            )
-        fig.suptitle("Occlusion | " + self.fig_title, fontsize=12)
-        return self.convert_fig_to_pil(fig)
-    
-    def gradcam(self):
-        layer_gradcam = LayerGradCam(self.model, self.model.layer3[1].conv2)
-        attributions_lgc = layer_gradcam.attribute(self.input, target=self.pred_label_idx)
-
-        #_ = viz.visualize_image_attr(attributions_lgc[0].cpu().permute(1,2,0).detach().numpy(),
-        #                            sign="all",
-        #                            title="Layer 3 Block 1 Conv 2")
-        upsamp_attr_lgc = LayerAttribution.interpolate(attributions_lgc, self.input.shape[2:])
-
-        fig, _ = viz.visualize_image_attr_multiple(upsamp_attr_lgc[0].cpu().permute(1,2,0).detach().numpy(),
-                                            self.transformed_img.permute(1,2,0).numpy(),
-                                            ["original_image","blended_heat_map","masked_image"],
-                                            ["all","positive","positive"],
-                                            show_colorbar=True,
+show_colorbar=True,
                                             titles=["Original", "Positive Attribution", "Masked"],
                                             fig_size=(18, 6))
         fig.suptitle("GradCAM layer3[1].conv2 | " + self.fig_title, fontsize=12)