| from llava.eval.run_llava import eval_model | |
| from llava.mm_utils import tokenizer_image_token, process_images, get_model_name_from_path | |
| import os | |
| model_path = "liuhaotian/llava-v1.5-7b" | |
| #prompt = "What are the things I should be cautious about when I visit here?" | |
| #prompt = "Could you help describe the input image?" | |
| prompt="Could you help describe the main object of the input image?" | |
| #prompt="In this view, identify and describe the object that is most likely for human interaction" | |
| #prompt = "Please describe the object with the green mask in the input image." | |
| # prompt = "Please describe the object coverd by the green mask." | |
| # prompt = "what is the object covered by the green mask?" | |
| #prompt = "what is the object in the red bounding box of the image" | |
| #prompt = "What is the object that is most likely interative with people?" | |
| #image_file = "https://llava-vl.github.io/static/images/view.jpg" | |
| image_file_list = ["images/WechatIMG2241.jpg","images/WechatIMG2242.jpg", "images/WechatIMG2243.jpg", "images/WechatIMG2244.jpg"] | |
| ego_list = os.listdir("./images/ego") | |
| ego_list = ["images/ego/"+ f for f in ego_list] | |
| exo_list = os.listdir("./images/exo") | |
| exo_list = ["images/exo/"+f for f in exo_list] | |
| images = ego_list | |
| print(ego_list) | |
| args = type('Args', (), { | |
| "model_path": model_path, | |
| "model_base": None, | |
| "model_name": get_model_name_from_path(model_path), | |
| "query": prompt, | |
| "conv_mode": None, | |
| "image_file": images, | |
| "sep": ",", | |
| "temperature": 0, | |
| "top_p": None, | |
| "num_beams": 1, | |
| "max_new_tokens": 512 | |
| })() | |
| eval_model(args) | |