update evaluation files

README.md

@@ -97,7 +97,7 @@ Download the pretrained model checkpoints
 
 | MiniGPT-v2 (after stage-2) | MiniGPT-v2 (after stage-3) | MiniGPT-v2 (online developing demo)| 
 |------------------------------|------------------------------|------------------------------|
-| [Download](https://drive.google.com/file/d/1Vi_E7ZtZXRAQcyz4f8E6LtLh2UXABCmu/view?usp=sharing) |[Download](https://drive.google.com/file/d/1jAbxUiyl04SFJMN4sF1vvUU69Etuz4qa/view?usp=sharing) | [Download](https://drive.google.com/file/d/1aVbfW7nkCSYx99_vCRyP1sOlQiWVSnAl/view?usp=sharing) |
+| [Download](https://drive.google.com/file/d/1Vi_E7ZtZXRAQcyz4f8E6LtLh2UXABCmu/view?usp=sharing) |[Download](https://drive.google.com/file/d/1HkoUUrjzFGn33cSiUkI-KcT-zysCynAz/view?usp=sharing) | [Download](https://drive.google.com/file/d/1aVbfW7nkCSYx99_vCRyP1sOlQiWVSnAl/view?usp=sharing) |
 
 
 For **MiniGPT-v2**, set the path to the pretrained checkpoint in the evaluation config file 

eval_configs/minigptv2_benchmark_evaluation.yaml

@@ -5,8 +5,8 @@ model:
   end_sym: "</s>"
   low_resource: False
   prompt_template: '[INST] {} [/INST]'
-  llama_model: "/ibex/project/c2133/llama_v2/llama-2-7b-chat-pytorch_update"
-  ckpt: "/ibex/project/c2133/minigpt_checkpoints/checkpoint_stage3_correct/checkpoint_10.pth"
+  llama_model: ""
+  ckpt: ""
   lora_r: 64
   lora_alpha: 16
 
@@ -23,8 +23,8 @@ datasets:
 
 evaluation_datasets:
   refcoco:
-    eval_file_path: /ibex/project/c2133/minigpt4_v2_dataset  
-    img_path: /ibex/ai/reference/CV/COCO/cocoapi/data/2014/images/jpeg/train   
+    eval_file_path: /path/to/eval/annotation/path  
+    img_path: /path/to/eval/image/path      
     max_new_tokens: 20
     batch_size: 10
   refcocog:
@@ -43,15 +43,15 @@ evaluation_datasets:
     max_new_tokens: 20
     batch_size: 10
   okvqa:
-    eval_file_path: /ibex/project/c2133/blip_dataset/ok_vqa_copy  
-    img_path: /ibex/ai/reference/CV/COCO/cocoapi/data/2017/images/jpeg/train    
+    eval_file_path: /path/to/eval/annotation/path  
+    img_path: /path/to/eval/image/path     
     max_new_tokens: 20
     batch_size: 10
   vizwiz:
-    eval_file_path: /ibex/project/c2133/minigpt4_v2_dataset/vizwiz/val.json 
-    img_path: /ibex/project/c2133/minigpt4_v2_dataset/vizwiz/val   
+    eval_file_path: /path/to/eval/annotation/path  
+    img_path: /path/to/eval/image/path    
     max_new_tokens: 20
-    batch_size: 10
+    batch_size: 100
   iconvqa:
     eval_file_path: /path/to/eval/annotation/path  
     img_path: /path/to/eval/image/path    
@@ -63,10 +63,10 @@ evaluation_datasets:
     max_new_tokens: 20
     batch_size: 10
   hm:
-    eval_file_path: /ibex/project/c2133/minigpt4_v2_dataset/hateful_meme/dev.jsonl  
-    img_path: /ibex/project/c2133/minigpt4_v2_dataset/hateful_meme   
+    eval_file_path: /path/to/eval/annotation/path  
+    img_path: /path/to/eval/image/path     
     max_new_tokens: 20
-    batch_size: 10
+    batch_size: 100
 
 run:
   task: image_text_pretrain

eval_scripts/eval_vqa.py

@@ -65,7 +65,7 @@ def list_of_str(arg):
             result['question_id'] = int(question_id)
             minigpt4_predict.append(result)
 
-    file_save_path= os.join(save_path,"okvqa.json")
+    file_save_path= os.path.join(save_path,"okvqa.json")
     with open(file_save_path,'w') as f:
         json.dump(minigpt4_predict, f)
 
@@ -245,7 +245,7 @@ def list_of_str(arg):
             if answer == label:
                 count+=1
             total+=1
-            
+
     print('hm val:', count / total * 100, flush=True)
     file_save_path = os.path.join(save_path, "hm.json")
     with open(file_save_path,'w') as f: