add tqdm download progress bar

requirements.txt

@@ -2,6 +2,7 @@ langchain==0.0.101
 torch==1.13.1
 torchvision==0.14.1
 wget==3.2
+tdqm
 accelerate
 addict
 albumentations

visual_chatgpt.py

@@ -44,6 +44,7 @@
 import numpy as np
 import matplotlib.pyplot as plt
 import wget
+from tqdm import tqdm
 
 VISUAL_CHATGPT_PREFIX = """Visual ChatGPT is designed to be able to assist with a wide range of text and visual related tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics. Visual ChatGPT is able to generate human-like text based on the input it receives, allowing it to engage in natural-sounding conversations and provide responses that are coherent and relevant to the topic at hand.
 
@@ -138,6 +139,18 @@
 os.makedirs('image', exist_ok=True)
 
 
+class ProgressBar:
+
+    def __init__(self, url):
+        self.progress_bar = None
+        print(f"Downloading checkpoints file from {url}")
+
+    def __call__(self, current_bytes, total_bytes, width):
+        if self.progress_bar is None:
+            self.progress_bar = tqdm(total=total_bytes, unit='B', unit_scale=True, unit_divisor=1024)#tqdm(total=total_mb, desc="MB")
+        self.progress_bar.update(current_bytes)
+
+
 def seed_everything(seed):
     random.seed(seed)
     np.random.seed(seed)
@@ -817,7 +830,7 @@ def __init__(self, device):
     def download_parameters(self):
         url = "https://dl.fbaipublicfiles.com/segment_anything/sam_vit_h_4b8939.pth"
         if not os.path.exists(self.model_checkpoint_path):
-            wget.download(url,out=self.model_checkpoint_path)
+            wget.download(url, out=self.model_checkpoint_path, bar=ProgressBar(url))
 
 
     def show_mask(self, mask: np.ndarray,image: np.ndarray,
@@ -1038,12 +1051,13 @@ def __init__(self, device):
     def download_parameters(self):
         url = "https://github.com/IDEA-Research/GroundingDINO/releases/download/v0.1.0-alpha/groundingdino_swint_ogc.pth"
         if not os.path.exists(self.model_checkpoint_path):
-            wget.download(url,out=self.model_checkpoint_path)
+            wget.download(url, out=self.model_checkpoint_path, bar=ProgressBar(url))
         config_url = "https://raw.githubusercontent.com/IDEA-Research/GroundingDINO/main/groundingdino/config/GroundingDINO_SwinT_OGC.py"
         if not os.path.exists(self.model_config_path):
-            wget.download(config_url,out=self.model_config_path)
-    def load_image(self,image_path):
-         # load image
+            wget.download(config_url, out=self.model_config_path, bar=ProgressBar(url))
+
+    def load_image(self, image_path):
+        # load image
         image_pil = Image.open(image_path).convert("RGB")  # load image
 
         transform = T.Compose(