try lisa

app.py

@@ -20,14 +20,10 @@ import gradio as gr
 
 import torch
 import torch.nn.functional as F
-import transformers
 from PIL import Image
 import numpy as np
 import time
 import threading
-import subprocess
-import sys
-import importlib
 
 from ncut_pytorch.backbone import extract_features, load_model
 from ncut_pytorch.backbone import MODEL_DICT, LAYER_DICT, RES_DICT
@@ -546,45 +542,54 @@ def run_fn(
     images = torch.stack(images)
     
     
-    # if is_lisa:
-    #     # LISA and Llava is not compatible with the current version of transformers
-    #     # please contact the author for update
-    #     # this is a dirty patch for the LISA model
+    if is_lisa:
+        import subprocess
+        import sys
+        import importlib
+        gr.Warning("LISA model is not compatible with the current version of transformers. Please contact the LISA and Llava author for update.")
+        gr.Warning("This is a dirty patch for the LISA model. switch to the old version of transformers.")
+        gr.Warning("Not garanteed to work.")
+        # LISA and Llava is not compatible with the current version of transformers
+        # please contact the author for update
+        # this is a dirty patch for the LISA model
         
-    #     # pre-import the SD3 pipeline
-    #     from diffusers import StableDiffusion3Pipeline
+        # pre-import the SD3 pipeline
+        from diffusers import StableDiffusion3Pipeline
         
-    #     # unloading the current transformers
-    #     for module in list(sys.modules.keys()):
-    #         if "transformers" in module:
-    #             del sys.modules[module]
+        # unloading the current transformers
+        for module in list(sys.modules.keys()):
+            if "transformers" in module:
+                del sys.modules[module]
             
 
-    #     def install_transformers_version(version, target_dir):
-    #         """Install a specific version of transformers to a target directory."""
-    #         if not os.path.exists(target_dir):
-    #             os.makedirs(target_dir)
+        def install_transformers_version(version, target_dir):
+            """Install a specific version of transformers to a target directory."""
+            if not os.path.exists(target_dir):
+                os.makedirs(target_dir)
             
-    #         # Use subprocess to run the pip command
-    #         # subprocess.check_call([sys.executable, '-m', 'pip', 'install', f'transformers=={version}', '-t', target_dir])
-    #         os.system(f"{sys.executable} -m pip install transformers=={version} -t {target_dir} >> /dev/null 2>&1")
+            # Use subprocess to run the pip command
+            # subprocess.check_call([sys.executable, '-m', 'pip', 'install', f'transformers=={version}', '-t', target_dir])
+            os.system(f"{sys.executable} -m pip install transformers=={version} -t {target_dir} >> /dev/null 2>&1")
 
-    #     target_dir = '/tmp/lisa_transformers_v433'
-    #     if not os.path.exists(target_dir):
-    #         install_transformers_version('4.33.0', target_dir)
+        target_dir = '/tmp/lisa_transformers_v433'
+        if not os.path.exists(target_dir):
+            install_transformers_version('4.33.0', target_dir)
 
-    #     # Add the new version path to sys.path
-    #     sys.path.insert(0, target_dir)
+        # Add the new version path to sys.path
+        sys.path.insert(0, target_dir)
         
-    #     transformers = importlib.import_module("transformers")
+        transformers = importlib.import_module("transformers")
 
-    # if not is_lisa:
-    #     # remove the LISA model from the sys.path
+    if not is_lisa:
+        import subprocess
+        import sys
+        import importlib
+        # remove the LISA model from the sys.path
             
-    #     if "/tmp/lisa_transformers_v433" in sys.path:
-    #         sys.path.remove("/tmp/lisa_transformers_v433")
+        if "/tmp/lisa_transformers_v433" in sys.path:
+            sys.path.remove("/tmp/lisa_transformers_v433")
         
-    #     transformers = importlib.import_module("transformers")
+        transformers = importlib.import_module("transformers")
         
     
     
@@ -1293,6 +1298,7 @@ with demo:
         gr.Markdown("- **Nyström** Normalized Cut, is a new approximation algorithm developed for large-scale graph cuts, a large-graph of million nodes can be processed in under 10s (cpu) or 2s (gpu).")
         gr.Markdown("- **spectral-tSNE** visualization, a new method to visualize the high-dimensional eigenvector space with 3D RGB cube. Color is aligned across images, color infers distance in representation.")
         
+        
     with gr.Row():
         with gr.Column():
             gr.Markdown("##### This demo is for `ncut-pytorch`, [Documentation](https://ncut-pytorch.readthedocs.io/) ")