feat:add env.py,try downgrade pytorch version

app.py

@@ -1,64 +1,16 @@
 
-import subprocess
 import os
 import sys
-import importlib.metadata
+from env import config_env
 
-def is_pkg_installed(pkg_name):
-    try:
-        importlib.metadata.distribution(pkg_name)
-        return True
-    except importlib.metadata.PackageNotFoundError:
-        return False
 
-packages_to_install = [
-    ('gradio',None),
-    ('numpy',None),
-    ('tensorflow', '2.9'),
-    ('keras', '2.9'),
-    ('opencv-python-headless', '4.5.5.64'),
-    ('python-dotenv', None),
-    ('torch', None),
-    ('torchvision', None),
-    ('xplique', None),
-    ('git+https://github.com/facebookresearch/segment-anything.git', None),
-    ('git+https://github.com/cocodataset/panopticapi.git', None),
-]
+config_env()
 
-env_name = os.path.basename(sys.prefix)
-if env_name == 'fossil': # in case pkgs installed to unexpected env during local dev
-    for package, version in packages_to_install:
-        package_spec = f"{package}=={version}" if version else package
-        if not is_pkg_installed(package):
-            #TODO
-            if package=='torch' or 'torchvision' or 'tensorflow':
-                subprocess.call(f"TMPDIR='../../../tmp/' pip install {package_spec}",shell=True) 
-            else:
-                subprocess.call(f"pip install {package_spec}".split()) 
-        else:
-            print(f"{package_spec} is already installed.")
-else:
-    print("Please use venv named 'fossil' in case pkgs installed to other unexpected envs or locations.")
-
-
-#print(os.getenv('SYSTEM'))
-
-'''
-if os.getenv('SYSTEM') == 'spaces':
-    subprocess.call('pip install tensorflow==2.9'.split())
-    subprocess.call('pip install keras==2.9'.split())
-    subprocess.call('pip install git+https://github.com/facebookresearch/segment-anything.git'.split())
-    subprocess.call('pip install opencv-python-headless==4.5.5.64'.split())
-    subprocess.call('pip install git+https://github.com/cocodataset/panopticapi.git'.split())
-    subprocess.call('pip install python-dotenv'.split())
-    subprocess.call('pip install torch torchvision '.split())
-    subprocess.call('pip install xplique'.split())
-'''
 
 import gradio as gr
 from huggingface_hub import snapshot_download
 import cv2 
-import dotenv 
+import dotenv
 dotenv.load_dotenv()
 import numpy as np
 import gradio as gr

env.py

@@ -0,0 +1,65 @@
+import os
+import subprocess
+import importlib.metadata
+
+
+def config_env():
+    packages_to_install = [
+        ('gradio',None),
+        ('numpy',None),
+        ('tensorflow', '2.9'),
+        ('keras', '2.9'),
+        ('opencv-python-headless', '4.5.5.64'),
+        ('python-dotenv', None),
+        ('torch', None),
+        ('torchvision', None),
+        ('xplique', None),
+        ('segment_anything', None),
+        ('panopticapi', None),
+    ]
+
+    name_to_command = {'segment_anything':'git+https://github.com/facebookresearch/segment-anything.git',
+                'panopticapi':'git+https://github.com/cocodataset/panopticapi.git',
+                'torch':'torch --index-url https://download.pytorch.org/whl/cu118',
+                'torchvision':'torchvision --index-url https://download.pytorch.org/whl/cu118',
+                }
+
+    env_name = os.path.basename(sys.prefix)
+    if env_name == 'fossil': # in case pkgs installed to unexpected env during local dev
+        for package, version in packages_to_install:
+            package_spec = f"{package}=={version}" if version else package
+            package_spec = name_to_command[package_spec] if package_spec in name_to_command
+            if not is_pkg_installed(package):
+                #TODO
+                if package=='torch' or 'torchvision' or 'tensorflow':
+                    # TMPDIR = 'home/username/tmp' for temporary compilation to prevent disk partition storage limit on zmachine
+                    subprocess.call(f"TMPDIR='../../../tmp/' pip install {package_spec}",shell=True) 
+                else:
+                    subprocess.call(f"pip install {package_spec}".split()) 
+            else:
+                print(f"{package_spec} is already installed.")
+    else:
+        print("Please use venv named 'fossil' in case pkgs installed to other unexpected envs or locations.")
+
+
+    #print(os.getenv('SYSTEM'))
+
+    '''
+    if os.getenv('SYSTEM') == 'spaces':
+        subprocess.call('pip install tensorflow==2.9'.split())
+        subprocess.call('pip install keras==2.9'.split())
+        subprocess.call('pip install git+https://github.com/facebookresearch/segment-anything.git'.split())
+        subprocess.call('pip install opencv-python-headless==4.5.5.64'.split())
+        subprocess.call('pip install git+https://github.com/cocodataset/panopticapi.git'.split())
+        subprocess.call('pip install python-dotenv'.split())
+        subprocess.call('pip install torch torchvision '.split())
+        subprocess.call('pip install xplique'.split())
+    '''
+
+
+def is_pkg_installed(pkg_name):
+    try:
+        importlib.metadata.distribution(pkg_name)
+        return True
+    except importlib.metadata.PackageNotFoundError:
+        return False

inference_sam.py

@@ -26,6 +26,7 @@ from huggingface_hub import snapshot_download
 if not os.path.exists('model'):
   REPO_ID='Serrelab/SAM_Leaves'
   token = os.environ.get('READ_TOKEN')
+  print(f"Read token:{token}")
   if token is None:
      print("warning! A read token in env variables is needed for authentication.")
   snapshot_download(repo_id=REPO_ID, token=token,repo_type='model',local_dir='model')

model/.gitattributes

@@ -1,35 +0,0 @@
-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
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-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
-*.model filter=lfs diff=lfs merge=lfs -text
-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
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-*.pickle filter=lfs diff=lfs merge=lfs -text
-*.pkl filter=lfs diff=lfs merge=lfs -text
-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
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-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text

model/README.md

@@ -1,37 +0,0 @@
----
-license: bigscience-openrail-m
-language:
-- en
-pipeline_tag: image-segmentation
----
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-
-## Model Details
-
-SAM trained with MSE and finetuned for leaves segmentation
-
-### Model Description
-
-
-
-
-- **Developed by:** Thomas Fel and I . Rodriguez
-
-- **Model type:** Semantic Segmentation 
-- **Language(s) (NLP):** [More Information Needed]
-
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-
-

model/sam_02-06_dice_mse_0.pth

@@ -1 +0,0 @@
-../../../../.cache/huggingface/hub/models--Serrelab--SAM_Leaves/blobs/920cc0f6b6d80b8dcd771cb39bdec6c6be9c44cc6fc95314ef20025b71e55a73