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Update to new Mars-Bench dataset structure with Author field
Browse files- app.py +19 -19
- data/classification.csv +10 -16
- data/detection.csv +4 -16
- data/segmentation.csv +9 -16
app.py
CHANGED
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@@ -49,7 +49,7 @@ def build_tab(df, name):
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datasets = sorted(df["Dataset"].unique().tolist())
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models = sorted(df["Model"].unique().tolist())
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organizations = sorted(df["Organization"].unique().tolist())
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-
metric_cols = [col for col in df.columns if col not in ["Model", "Organization", "Dataset", "
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# Create pivoted dataframe
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pivoted_data = []
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@@ -57,17 +57,17 @@ def build_tab(df, name):
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for org in organizations:
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model_org_data = df[(df["Model"] == model) & (df["Organization"] == org)]
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if not model_org_data.empty:
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# Get
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-
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author_link = model_org_data["Author Link"].values[0]
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# Format as markdown link if author_link exists
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if pd.notna(author_link) and author_link.strip():
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author_display = f"[{
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else:
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author_display =
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row = {"Model": model, "Organization": org, "
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for dataset in datasets:
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dataset_data = model_org_data[model_org_data["Dataset"] == dataset]
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if not dataset_data.empty:
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@@ -88,7 +88,7 @@ def build_tab(df, name):
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for metric in metric_cols:
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metric_combo_cols.append(f"{dataset} ({metric})")
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-
all_cols = ["Model", "Organization", "
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with gr.TabItem(name, elem_id="llm-benchmark-tab-table"):
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with gr.Row():
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@@ -100,7 +100,7 @@ def build_tab(df, name):
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)
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# Column selector for base columns only (not dataset+metric combos)
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-
base_cols = ["Model", "Organization", "
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col_selector = gr.CheckboxGroup(
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choices=base_cols,
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value=base_cols,
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@@ -108,10 +108,10 @@ def build_tab(df, name):
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elem_classes="column-select"
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)
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# Set datatype to 'markdown' for
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datatypes = []
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for col in pivoted_df.columns:
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-
if col == "
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datatypes.append("markdown")
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else:
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datatypes.append("str")
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@@ -246,7 +246,7 @@ custom_css = """
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min-width: 120px;
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}
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/* Style links in
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#leaderboard-table a {
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color: #0066cc;
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text-decoration: none;
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@@ -354,10 +354,10 @@ with demo:
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)
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with gr.Column():
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label="
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placeholder="e.g., K. He",
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info="Name of the
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)
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submit_author_link = gr.Textbox(
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label="Author Page Link (Optional)",
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@@ -404,9 +404,9 @@ with demo:
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We'll review your submission and add it to the leaderboard if approved.
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""")
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def generate_submission_text(task, model, org, dataset,
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if not all([task, model, org, dataset,
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return "❌ Error: Please fill in all required fields (Task Type, Model Name, Organization, Dataset,
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submission_text = f"""## New Model Submission
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@@ -414,7 +414,7 @@ with demo:
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**Model Name:** {model}
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**Organization:** {org}
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**Dataset:** {dataset}
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**
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**Author Page Link:** {author_link if author_link else "N/A"}
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### Metrics
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@@ -439,7 +439,7 @@ with demo:
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generate_btn.click(
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generate_submission_text,
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inputs=[submit_task, submit_model, submit_org, submit_dataset,
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submit_author_link, submit_metrics, submit_paper, submit_code, submit_email, submit_notes],
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outputs=submission_output
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)
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datasets = sorted(df["Dataset"].unique().tolist())
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models = sorted(df["Model"].unique().tolist())
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organizations = sorted(df["Organization"].unique().tolist())
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+
metric_cols = [col for col in df.columns if col not in ["Model", "Organization", "Dataset", "Author", "Author Link"]]
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# Create pivoted dataframe
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pivoted_data = []
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for org in organizations:
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model_org_data = df[(df["Model"] == model) & (df["Organization"] == org)]
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if not model_org_data.empty:
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# Get Author and Author Link from the first entry (they should be the same for model+org)
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author = model_org_data["Author"].values[0]
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author_link = model_org_data["Author Link"].values[0]
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# Format as markdown link if author_link exists
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if pd.notna(author_link) and author_link.strip():
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author_display = f"[{author}]({author_link})"
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else:
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author_display = author
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row = {"Model": model, "Organization": org, "Author": author_display}
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for dataset in datasets:
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dataset_data = model_org_data[model_org_data["Dataset"] == dataset]
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if not dataset_data.empty:
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for metric in metric_cols:
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metric_combo_cols.append(f"{dataset} ({metric})")
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all_cols = ["Model", "Organization", "Author"] + metric_combo_cols
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with gr.TabItem(name, elem_id="llm-benchmark-tab-table"):
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with gr.Row():
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)
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# Column selector for base columns only (not dataset+metric combos)
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base_cols = ["Model", "Organization", "Author"]
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col_selector = gr.CheckboxGroup(
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choices=base_cols,
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value=base_cols,
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elem_classes="column-select"
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)
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# Set datatype to 'markdown' for Author column to enable clickable links
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datatypes = []
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for col in pivoted_df.columns:
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if col == "Author":
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datatypes.append("markdown")
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else:
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datatypes.append("str")
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min-width: 120px;
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}
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/* Style links in Author column */
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#leaderboard-table a {
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color: #0066cc;
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text-decoration: none;
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)
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with gr.Column():
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submit_author = gr.Textbox(
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label="Author",
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placeholder="e.g., K. He",
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info="Name of the author"
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)
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submit_author_link = gr.Textbox(
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label="Author Page Link (Optional)",
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We'll review your submission and add it to the leaderboard if approved.
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""")
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def generate_submission_text(task, model, org, dataset, author, author_link, metrics, paper, code, email, notes):
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if not all([task, model, org, dataset, author, metrics, email]):
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return "❌ Error: Please fill in all required fields (Task Type, Model Name, Organization, Dataset, Author, Metrics, Contact Email)"
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submission_text = f"""## New Model Submission
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**Model Name:** {model}
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**Organization:** {org}
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**Dataset:** {dataset}
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**Author:** {author}
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**Author Page Link:** {author_link if author_link else "N/A"}
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### Metrics
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generate_btn.click(
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generate_submission_text,
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inputs=[submit_task, submit_model, submit_org, submit_dataset, submit_author,
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submit_author_link, submit_metrics, submit_paper, submit_code, submit_email, submit_notes],
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outputs=submission_output
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)
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data/classification.csv
CHANGED
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@@ -1,16 +1,10 @@
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Model,Organization,Dataset,Accuracy,F1-Score,
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SqueezeNet,DeepMind,Atmospheric Dust,87.2,86.3,F. Iandola,https://scholar.google.com/citations?user=LvWAIwUAAAAJ
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ResNet-50,Microsoft,Martian Frost,85.6,84.8,K. He,https://kaiminghe.github.io/
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ViT-Base,Google,Martian Frost,87.9,86.9,A. Dosovitskiy,https://scholar.google.com/citations?user=UfvnhKcAAAAJ
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Swin-T,Microsoft,Martian Frost,88.4,87.5,Z. Liu,https://scholar.google.com/citations?user=nHh9PSsAAAAJ
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InceptionV3,Google,Martian Frost,86.7,85.8,C. Szegedy,https://scholar.google.com/citations?user=3QeF7mAAAAAJ
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SqueezeNet,DeepMind,Martian Frost,84.3,83.4,F. Iandola,https://scholar.google.com/citations?user=LvWAIwUAAAAJ
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Model,Organization,Dataset,Accuracy,F1-Score,Author,Author Link
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Under Construction,Under Construction,atmospheric_dust_cls_edr,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,atmospheric_dust_cls_rdr,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,change_cls_ctx,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,change_cls_hirise,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,domars16k,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,frost_cls,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,landmark_cls,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,surface_cls,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,surface_multi_label_cls,Under Construction,Under Construction,Under Construction,
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data/detection.csv
CHANGED
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Model,Organization,Dataset,mAP,IoU,
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RetinaNet,Meta,Mars Crater,79.3,0.73,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
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SSD,Google,Mars Crater,77.8,0.71,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ
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Faster R-CNN,Meta,Rover Component,75.6,0.69,S. Ren,https://scholar.google.com/citations?user=L_hq4a0AAAAJ
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YOLOv5,Ultralytics,Rover Component,77.3,0.71,G. Jocher,https://github.com/glenn-jocher
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DETR,Meta,Rover Component,78.9,0.73,N. Carion,https://scholar.google.com/citations?user=p1wMCUUAAAAJ
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RetinaNet,Meta,Rover Component,76.7,0.70,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
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SSD,Google,Rover Component,75.1,0.68,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ
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Faster R-CNN,Meta,Geological Feature,73.4,0.67,S. Ren,https://scholar.google.com/citations?user=L_hq4a0AAAAJ
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YOLOv5,Ultralytics,Geological Feature,75.1,0.69,G. Jocher,https://github.com/glenn-jocher
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DETR,Meta,Geological Feature,76.7,0.71,N. Carion,https://scholar.google.com/citations?user=p1wMCUUAAAAJ
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RetinaNet,Meta,Geological Feature,74.5,0.68,T. Lin,https://scholar.google.com/citations?user=7zQoaFkAAAAJ
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SSD,Google,Geological Feature,73.0,0.67,W. Liu,https://scholar.google.com/citations?user=PQ7QBjYAAAAJ
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Model,Organization,Dataset,mAP,IoU,Author,Author Link
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Under Construction,Under Construction,boulder_det,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,conequest_det,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,dust_devil_det,Under Construction,Under Construction,Under Construction,
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data/segmentation.csv
CHANGED
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@@ -1,16 +1,9 @@
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Model,Organization,Dataset,Dice Score,IoU,
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SegFormer,NVIDIA,Dust Storm,0.83,0.71,E. Xie,https://scholar.google.com/citations?user=txgkZ0kAAAAJ
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HRNet,Microsoft,Dust Storm,0.82,0.70,J. Wang,https://scholar.google.com/citations?user=aYKQn88AAAAJ
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U-Net,OpenAI,Geological Feature,0.81,0.68,O. Ronneberger,https://scholar.google.com/citations?user=MXXkjXkAAAAJ
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DeepLabV3+,Google,Geological Feature,0.83,0.70,L. Chen,https://scholar.google.com/citations?user=WicCTRsAAAAJ
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Mask R-CNN,Meta,Geological Feature,0.84,0.72,K. He,https://kaiminghe.github.io/
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SegFormer,NVIDIA,Geological Feature,0.82,0.69,E. Xie,https://scholar.google.com/citations?user=txgkZ0kAAAAJ
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HRNet,Microsoft,Geological Feature,0.81,0.68,J. Wang,https://scholar.google.com/citations?user=aYKQn88AAAAJ
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Model,Organization,Dataset,Dice Score,IoU,Author,Author Link
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Under Construction,Under Construction,boulder_seg,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,conequest_seg,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,crater_binary_seg,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,crater_multi_seg,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,mars_seg_mer,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,mars_seg_msl,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,mmls,Under Construction,Under Construction,Under Construction,
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Under Construction,Under Construction,s5mars,Under Construction,Under Construction,Under Construction,
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