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Parent(s):
2bac6b2
brute force revert commit
Browse files- app.py +21 -42
- src/utils.py +1 -4
app.py
CHANGED
@@ -28,8 +28,6 @@ def main():
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# Main App Components
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title = gr.Markdown("# Saliency evaluation - experiment 1")
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user_state = gr.State(0)
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images_list = gr.State([])
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current_image_id = gr.State(0)
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answers = gr.State([])
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start_time = gr.State(time.time())
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@@ -70,13 +68,11 @@ def main():
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with gr.Row():
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count = user_state if isinstance(user_state, int) else user_state.value
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images = load_image_and_saliency(count, data_dir)
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saliency_sidu = gr.Image(images[5], elem_classes="main-image", visible=False)
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saliency_rise = gr.Image(images[4], elem_classes="main-image", visible=False)
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with gr.Row():
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@@ -92,7 +88,7 @@ def main():
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def update_images(user_state):
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count = user_state if isinstance(user_state, int) else user_state.value
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if count < config['dataset'][config['dataset']['name']]['n_classes']:
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-
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# image examples
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images = load_example_images(count, data_dir)
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@@ -120,16 +116,14 @@ def main():
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count = user_state if isinstance(user_state, int) else user_state.value
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if count < config['dataset'][config['dataset']['name']]['n_classes']:
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images = load_image_and_saliency(count, data_dir)
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saliency_rise = gr.Image(images[4], elem_classes="main-image", visible=True)
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return current_image_id, target_img, saliency_gradcam, saliency_lime, saliency_rise, saliency_sidu
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else:
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return
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def update_state(state):
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count = state if isinstance(state, int) else state.value
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@@ -154,11 +148,11 @@ def main():
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def hide_view():
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target_img = gr.Image(images[
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saliency_gradcam = gr.Image(images[
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saliency_lime = gr.Image(images[
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saliency_sidu = gr.Image(images[
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saliency_rise = gr.Image(images[
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question = gr.Markdown(f"### Sort the following saliency maps according to which of them better explains the class {class_names[count]}.", visible=False)
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dropdown1 = gr.Dropdown(choices=options, label="grad-cam", visible=False)
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dropdown2 = gr.Dropdown(choices=options, label="lime", visible=False)
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@@ -205,11 +199,9 @@ def main():
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info_to_push = {
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"user_id": time.time(),
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"answer": {i: answer for i, answer in enumerate(answers)},
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"
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"duration": duration,
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}
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print(f"Saving results {info_to_push}")
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# Save the results into huggingface hub
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with scheduler.lock:
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with JSON_DATASET_PATH.open("a") as f:
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@@ -235,11 +227,6 @@ def main():
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answers.append(rank)
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return answers
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def add_image_id(id, images_list):
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images_list.append(id.value)
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print(f"Image ID: {id.value} added to the list")
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return images_list
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submit_button.click(
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check_answer,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4]
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@@ -251,10 +238,6 @@ def main():
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add_answer,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4, answers],
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outputs=answers
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).then(
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add_image_id,
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inputs=[current_image_id, images_list],
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outputs=images_list
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).then(
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update_img_label,
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inputs=user_state,
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@@ -282,7 +265,7 @@ def main():
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).then(
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update_saliencies,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4, user_state],
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outputs={
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).then(
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update_questions,
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inputs=user_state,
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@@ -295,10 +278,6 @@ def main():
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finish_button.click(
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add_answer, inputs=[dropdown1, dropdown2, dropdown3, dropdown4, answers],outputs=answers
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).then(
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add_image_id,
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inputs=[current_image_id, images_list],
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outputs=images_list
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).then(
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save_results, inputs=answers
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).then(
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@@ -308,4 +287,4 @@ def main():
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demo.launch()
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if __name__ == "__main__":
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main()
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# Main App Components
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title = gr.Markdown("# Saliency evaluation - experiment 1")
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user_state = gr.State(0)
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answers = gr.State([])
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start_time = gr.State(time.time())
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with gr.Row():
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count = user_state if isinstance(user_state, int) else user_state.value
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images = load_image_and_saliency(count, data_dir)
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target_img = gr.Image(images[0], elem_classes="main-image delay", visible=False)
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saliency_gradcam = gr.Image(images[1], elem_classes="main-image", visible=False)
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saliency_lime = gr.Image(images[2], elem_classes="main-image", visible=False)
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saliency_sidu = gr.Image(images[4], elem_classes="main-image", visible=False)
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saliency_rise = gr.Image(images[3], elem_classes="main-image", visible=False)
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with gr.Row():
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def update_images(user_state):
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count = user_state if isinstance(user_state, int) else user_state.value
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if count < config['dataset'][config['dataset']['name']]['n_classes']:
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images = load_image_and_saliency(count, data_dir)
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# image examples
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images = load_example_images(count, data_dir)
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count = user_state if isinstance(user_state, int) else user_state.value
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if count < config['dataset'][config['dataset']['name']]['n_classes']:
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images = load_image_and_saliency(count, data_dir)
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target_img = gr.Image(images[0], elem_classes="main-image", visible=True)
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saliency_gradcam = gr.Image(images[1], elem_classes="main-image", visible=True)
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saliency_lime = gr.Image(images[2], elem_classes="main-image", visible=True)
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saliency_sidu = gr.Image(images[4], elem_classes="main-image", visible=True)
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saliency_rise = gr.Image(images[3], elem_classes="main-image", visible=True)
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return target_img, saliency_gradcam, saliency_lime, saliency_rise, saliency_sidu
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else:
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return target_img, saliency_gradcam, saliency_lime, saliency_rise, saliency_sidu
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def update_state(state):
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count = state if isinstance(state, int) else state.value
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def hide_view():
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target_img = gr.Image(images[0], elem_classes="main-image", visible=False)
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saliency_gradcam = gr.Image(images[1], elem_classes="main-image", visible=False)
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saliency_lime = gr.Image(images[2], elem_classes="main-image", visible=False)
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saliency_sidu = gr.Image(images[4], elem_classes="main-image", visible=False)
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saliency_rise = gr.Image(images[3], elem_classes="main-image", visible=False)
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question = gr.Markdown(f"### Sort the following saliency maps according to which of them better explains the class {class_names[count]}.", visible=False)
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dropdown1 = gr.Dropdown(choices=options, label="grad-cam", visible=False)
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dropdown2 = gr.Dropdown(choices=options, label="lime", visible=False)
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info_to_push = {
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"user_id": time.time(),
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"answer": {i: answer for i, answer in enumerate(answers)},
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"duration": duration
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}
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# Save the results into huggingface hub
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with scheduler.lock:
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with JSON_DATASET_PATH.open("a") as f:
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answers.append(rank)
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return answers
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submit_button.click(
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check_answer,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4]
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add_answer,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4, answers],
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outputs=answers
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).then(
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update_img_label,
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inputs=user_state,
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).then(
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update_saliencies,
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inputs=[dropdown1, dropdown2, dropdown3, dropdown4, user_state],
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outputs={target_img, saliency_gradcam, saliency_lime, saliency_sidu, saliency_rise},
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).then(
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update_questions,
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inputs=user_state,
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finish_button.click(
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add_answer, inputs=[dropdown1, dropdown2, dropdown3, dropdown4, answers],outputs=answers
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).then(
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save_results, inputs=answers
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).then(
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demo.launch()
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if __name__ == "__main__":
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main()
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src/utils.py
CHANGED
@@ -19,7 +19,7 @@ def load_image_and_saliency(class_idx, data_dir):
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lime_image = os.path.join(data_dir, 'saliency', 'lime', images[id])
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sidu_image = os.path.join(data_dir, 'saliency', 'sidu', images[id])
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rise_image = os.path.join(data_dir, 'saliency', 'rise', images[id])
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return
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def load_example_images(class_idx, data_dir, max_images=16):
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path = os.path.join(data_dir, 'images', str(class_idx))
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@@ -41,6 +41,3 @@ def load_csv_concepts(data_dir):
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data = pd.read_csv(os.path.join(data_dir, 'concepts_by_class.csv'))
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return data
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lime_image = os.path.join(data_dir, 'saliency', 'lime', images[id])
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sidu_image = os.path.join(data_dir, 'saliency', 'sidu', images[id])
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rise_image = os.path.join(data_dir, 'saliency', 'rise', images[id])
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return image, gradcam_image, lime_image, sidu_image, rise_image
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def load_example_images(class_idx, data_dir, max_images=16):
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path = os.path.join(data_dir, 'images', str(class_idx))
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data = pd.read_csv(os.path.join(data_dir, 'concepts_by_class.csv'))
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return data
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