Update app.py

app.py

@@ -16,4 +16,57 @@ import gradio as gr
 !wget -O sam2_hiera_tiny.pt "https://dl.fbaipublicfiles.com/segment_anything_2/072824/sam2_hiera_tiny.pt"
 !wget -O sam2_hiera_small.pt "https://dl.fbaipublicfiles.com/segment_anything_2/072824/sam2_hiera_small.pt"
 !wget -O sam2_hiera_base_plus.pt "https://dl.fbaipublicfiles.com/segment_anything_2/072824/sam2_hiera_base_plus.pt"
-!wget -O sam2_hiera_large.pt "https://dl.fbaipublicfiles.com/segment_anything_2/072824/sam2_hiera_large.pt"
+!wget -O sam2_hiera_large.pt "https://dl.fbaipublicfiles.com/segment_anything_2/072824/sam2_hiera_large.pt"
+
+import os
+#import gradio as gr
+import numpy as np
+import pandas as pd
+import cv2
+import torch
+import torch.nn as nn
+from PIL import Image
+import matplotlib.pyplot as plt
+import seaborn as sns
+from fastai.vision import *
+from fastai.vision.all import *
+from sklearn.metrics import confusion_matrix
+from sklearn.model_selection import train_test_split
+import tensorflow as tf
+import re
+import json
+import ast
+import openai
+import tiktoken
+import shutil
+import concurrent
+import textwrap
+from time import sleep
+from csv import writer
+from tqdm import tqdm
+from scipy import spatial
+from pptx import Presentation  # for PowerPoint
+from PyPDF2 import PdfReader
+from openai import OpenAI
+from IPython.display import display, Markdown, Latex, HTML
+from transformers import GPT2Tokenizer
+#from transformers import AutoTokenizer
+from google.colab import files  # for uploading files
+from termcolor import colored  # for colored text output
+
+%matplotlib inline
+%config InlineBackend.figure_format='retina'
+
+%cd /content/segment-anything-2
+
+from sam2.build_sam import build_sam2
+from sam2.sam2_image_predictor import SAM2ImagePredictor
+
+sam2_checkpoint = "sam2_hiera_small.pt"
+model_cfg = "sam2_hiera_s.yaml"
+
+sam2_model = build_sam2(model_cfg, sam2_checkpoint, device="cuda")
+predictor = SAM2ImagePredictor(sam2_model)
+
+checkpoint_path = "/root/.cache/kagglehub/models/ybhavsar/newsegmentation/PyTorch/default/1/sam2_lr0.0001_wd0.01_900.torch"
+predictor.model.load_state_dict(torch.load(checkpoint_path))