Updated to newest gradio version and version fixed the dependencies.

.gitignore

@@ -1 +1,3 @@
-.vscode
+.vscode
+app_copy.py
+__pycache__

app.py

@@ -1,6 +1,3 @@
-# AUTOGENERATED! DO NOT EDIT! File to edit: ../main.ipynb.
-
-# %% auto 0
 __all__ = [
     "ORGAN",
     "IMAGE_SIZE",
@@ -23,7 +20,6 @@ __all__ = [
     "to_oberlay_image",
 ]
 
-# %% ../main.ipynb 1
 import numpy as np
 import pandas as pd
 import skimage
@@ -32,7 +28,6 @@ import segmentation_models_pytorch as smp
 
 import gradio as gr
 
-# %% ../main.ipynb 2
 ORGAN = "kidney"
 IMAGE_SIZE = 512
 MODEL_NAME = "unetpp_b4_th60_d9414.pkl"
@@ -40,7 +35,6 @@ THRESHOLD = float(MODEL_NAME.split("_")[2][2:]) / 100.0
 CODES = ["Background", "FTU"]  # FTU = functional tissue unit
 
 
-# %% ../main.ipynb 3
 def x_getter(r):
     return r["fnames"]
 
@@ -59,11 +53,9 @@ def splitter(model):
     return L([enc_params, untrained_params])
 
 
-# %% ../main.ipynb 4
 learn = load_learner(MODEL_NAME)
 
 
-# %% ../main.ipynb 5
 def make3D(t: np.array) -> np.array:
     t = np.expand_dims(t, axis=2)
     t = np.concatenate((t, t, t), axis=2)
@@ -126,7 +118,6 @@ def to_oberlay_image(data):
     return img
 
 
-# %% ../main.ipynb 6
 title = "Glomerulus Segmentation"
 description = """
 A web app that segments glomeruli in histological kidney slices!
@@ -137,24 +128,18 @@ The provided example images are random subset of kidney slices from the [Human P
 
 Here is my corresponding [blog post](https://fhatje.github.io/posts/glomseg/train_model.html).
 """
-# article="<p style='text-align: center'><a href='Blog post URL' target='_blank'>Blog post</a></p>"
+
 examples = [str(p) for p in get_image_files("example_images")]
 interpretation = "default"
 
-# %% ../main.ipynb 7
 demo = gr.Interface(
     fn=predict,
-    inputs=gr.components.Image(shape=(IMAGE_SIZE, IMAGE_SIZE)),
+    inputs=gr.components.Image(width=IMAGE_SIZE, height=IMAGE_SIZE),
     outputs=[gr.components.Image(), gr.components.DataFrame()],
     title=title,
     description=description,
     examples=examples,
-    interpretation=interpretation,
-    # Fixes error when set to True:
-    # https://github.com/gradio-app/gradio/pull/1949
-    # but generated file names are too long
-    _api_mode=False,
+    # interpretation=interpretation,
 )
 
-# %% ../main.ipynb 9
 demo.launch()

requirements.txt

@@ -1,3 +1,3 @@
-fastai
-scikit-image
-segmentation-models-pytorch
+fastai==2.9.7
+scikit-image==0.19.3
+segmentation-models-pytorch==0.3.0