Upload app.py after modify fastsam imports

app.py

@@ -1,31 +1,14 @@
 import os
-import cv2
 import numpy as np
 from PIL import Image
 import gradio as gr
-import json
-import matplotlib.pyplot as plt
-import subprocess
-
-repo_url = "https://github.com/CASIA-IVA-Lab/FastSAM.git"
-target_directory = "./FastSAM"
-subprocess.run(['git', 'clone', repo_url, target_directory])
-os.chdir('./FastSAM')
-print('pwd: ', os.getcwd())
-
-from fastsam import FastSAM, FastSAMPrompt 
-import ast
 import torch
-from PIL import Image
-from utils.tools import convert_box_xywh_to_xyxy
+import matplotlib.pyplot as plt
+from fastsam import FastSAM, FastSAMPrompt
 
 def gradio_fn(pil_input_img):
     # load model
     model = FastSAM('./weights/FastSAM.pt')
-    args_point_prompt = ast.literal_eval("[[0,0]]")
-    args_box_prompt = convert_box_xywh_to_xyxy(ast.literal_eval("[[0,0,0,0]]"))
-    args_point_label = ast.literal_eval("[0]")
-    args_text_prompt = None
     input = pil_input_img
     input = input.convert("RGB")
     everything_results = model(
@@ -40,19 +23,7 @@ def gradio_fn(pil_input_img):
     points = None
     point_label = None
     prompt_process = FastSAMPrompt(input, everything_results, device="cpu")
-    if args_box_prompt[0][2] != 0 and args_box_prompt[0][3] != 0:
-            ann = prompt_process.box_prompt(bboxes=args_box_prompt)
-            bboxes = args_box_prompt
-    elif args_text_prompt != None:
-        ann = prompt_process.text_prompt(text=args_text_prompt)
-    elif args_point_prompt[0] != [0, 0]:
-        ann = prompt_process.point_prompt(
-            points=args_point_prompt, pointlabel=args_point_label
-        )
-        points = args_point_prompt
-        point_label = args_point_label
-    else:
-        ann = prompt_process.everything_prompt()
+    ann = prompt_process.everything_prompt()
     prompt_process.plot(
         annotations=ann,
         output_path="./output.jpg",
@@ -73,4 +44,6 @@ demo = gr.Interface(fn=gradio_fn,
                     description="- **FastSAM** model that returns segmented RGB image of given input image. \
                                  - **Credits** : \
                                     - https://huggingface.co/An-619 \
-                                    - https://github.com/CASIA-IVA-Lab/FastSAM")
+                                    - https://github.com/CASIA-IVA-Lab/FastSAM")
+
+demo.launch(share=True)