add A2/A3 existing results

app.py

@@ -30,9 +30,14 @@ with block:
     gr.Markdown(
         LEADERBORAD_INTRODUCTION
     )
-    with gr.Tab("Perception-A1-dev"):
+    with gr.Tab("Perception (A1, dev)"):
         gr.DataFrame(pd.read_csv("qbench_a1_single_dev.csv"))
-    with gr.Tab("Perception-A1-test"):
+    with gr.Tab("Perception (A1,test)"):
         gr.DataFrame(pd.read_csv("qbench_a1_single_test.csv"))
+    with gr.Tab("Description (A2)"):
+        gr.DataFrame(pd.read_csv("qbench_a2_single.csv"))
+    with gr.Tab("Assessment (A3)"):
+        gr.DataFrame(pd.read_csv("qbench_a3_single.csv"))
+    
     
 block.launch(share=True)

qbench_a2_single.csv

@@ -0,0 +1,22 @@
+Model,Completeness,Precision,Relevance,Sum
+InfiMM (Zephyr-7B),0.77,1.08,1.71,3.58
+Emu2-Chat (LLaMA-33B),1.07,1.24,1.88,4.19
+Fuyu-8B (Persimmon-8B),0.88,0.83,1.82,3.53
+BakLLava (Mistral-7B),1.0,0.77,1.61,3.38
+SPHINX,0.79,1.14,1.72,3.65
+mPLUG-Owl2 (LLaMA-7B),1.06,1.24,1.36,3.67
+LLaVA-v1.5 (Vicuna-v1.5-7B),0.9,1.13,1.18,3.21
+LLaVA-v1.5 (Vicuna-v1.5-13B),0.91,1.28,1.29,3.47
+InternLM-XComposer-VL (InternLM),1.08,1.26,1.87,4.21
+IDEFICS-Instruct (LLaMA-7B),0.83,1.03,1.33,3.18
+Qwen-VL (QwenLM),0.98,0.75,1.63,3.36
+Shikra (Vicuna-7B),0.89,1.11,1.33,3.34
+Otter-v1 (MPT-7B),0.96,0.83,1.83,3.61
+Kosmos-2,1.12,1.06,1.85,4.03
+InstructBLIP (Flan-T5-XL),0.87,1.04,1.11,3.02
+InstructBLIP (Vicuna-7B),0.79,1.21,0.84,2.84
+VisualGLM-6B (GLM-6B),0.82,0.97,1.21,2.99
+mPLUG-Owl (LLaMA-7B),1.06,1.28,1.6,3.94
+LLaMA-Adapter-V2,0.85,1.15,1.44,3.45
+LLaVA-v1 (Vicuna-13B),0.91,1.25,1.6,3.76
+MiniGPT-4 (Vicuna-13B),1.0,1.26,1.41,3.67

qbench_a3_single.csv

@@ -0,0 +1,23 @@
+Model,KONiQ-10k,SPAQ,LIVE-FB,LIVE-ITW,CGIQA-6K,AGIQA-3K
+NIQE,0.316/0.377,0.693/0.669,0.211/0.288,0.480/0.451,0.075/0.056,0.562/0.517
+CLIP-ViT-Large-14,0.468/0.505,0.385/0.389,0.218/0.237,0.307/0.308,0.285/0.290,0.436/0.458
+InfiMM (Zephyr-7B),0.507/0.547,0.616/0.633,0.269/0.299,0.548/0.580,0.229/0.245,0.706/0.767
+Emu2-Chat (LLaMA-33B),0.664/0.714,0.712/0.698,0.355/0.341,0.597/0.611,0.224/0.269,0.759/0.751
+Fuyu-8B (Persimmon-8B),0.124/0.123,0.125/0.179,0.164/0.133,0.225/0.176,0.118/0.116,0.368/0.317
+BakLLava (Mistral-7B),0.389/0.390,0.406/0.398,0.227/0.216,0.335/0.337,0.179/0.209,0.542/0.561
+mPLUG-Owl2 (LLaMA-7B),0.196/0.252,0.589/0.614,0.217/0.286,0.293/0.342,-0.024/-0.032,0.473/0.492
+LLaVA-v1.5 (Vicuna-v1.5-7B),0.463/0.459,0.443/0.467,0.305/0.321,0.344/0.358,0.321/0.333,0.672/0.738
+LLaVA-v1.5 (Vicuna-v1.5-13B),0.448/0.460,0.563/0.584,0.310/0.339,0.445/0.481,0.285/0.297,0.664/0.754
+InternLM-XComposer-VL (InternLM),0.564/0.615,0.730/0.750,0.360/0.416,0.612/0.676,0.243/0.265,0.732/0.775
+IDEFICS-Instruct (LLaMA-7B),0.375/0.400,0.474/0.484,0.235/0.240,0.409/0.428,0.244/0.227,0.562/0.622
+Qwen-VL (QwenLM),0.470/0.546,0.676/0.669,0.298/0.338,0.504/0.532,0.273/0.284,0.617/0.686
+Shikra (Vicuna-7B),0.314/0.307,0.320/0.337,0.237/0.241,0.322/0.336,0.198/0.201,0.640/0.661
+Otter-v1 (MPT-7B),0.406/0.406,0.436/0.441,0.143/0.142,-0.008/0.018,0.254/0.264,0.475/0.481
+Kosmos-2,0.255/0.281,0.644/0.641,0.196/0.195,0.358/0.368,0.210/0.225,0.489/0.491
+InstructBLIP (Flan-T5-XL),0.334/0.362,0.582/0.599,0.248/0.267,0.113/0.113,0.167/0.188,0.378/0.400
+InstructBLIP (Vicuna-7B),0.359/0.437,0.683/0.689,0.200/0.283,0.253/0.367,0.263/0.304,0.629/0.663
+VisualGLM-6B (GLM-6B),0.247/0.234,0.498/0.507,0.146/0.154,0.110/0.116,0.209/0.183,0.342/0.349
+mPLUG-Owl (LLaMA-7B),0.409/0.427,0.634/0.644,0.241/0.271,0.437/0.487,0.148/0.180,0.687/0.711
+LLaMA-Adapter-V2,0.354/0.363,0.464/0.506,0.275/0.329,0.298/0.360,0.257/0.271,0.604/0.666
+LLaVA-v1 (Vicuna-13B),0.462/0.457,0.442/0.462,0.264/0.280,0.404/0.417,0.208/0.237,0.626/0.684
+MiniGPT-4 (Vicuna-13B),0.239/0.257,0.238/0.253,0.170/0.183,0.339/0.340,0.252/0.246,0.572/0.591