first deploy pls work

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* 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
+*.keras filter=lfs diff=lfs merge=lfs -text

.idea/.gitignore

@@ -0,0 +1,3 @@
+# Default ignored files
+/shelf/
+/workspace.xml

.idea/Surgical-Tool-Segmentation.iml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="jdk" jdkName="Python 3.11 (CU-There)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

@@ -0,0 +1,6 @@
+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/misc.xml

@@ -0,0 +1,7 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="Black">
+    <option name="sdkName" value="Python 3.11 (CU-There)" />
+  </component>
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.11 (CU-There)" project-jdk-type="Python SDK" />
+</project>

.idea/modules.xml

@@ -0,0 +1,8 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Surgical-Tool-Segmentation.iml" filepath="$PROJECT_DIR$/.idea/Surgical-Tool-Segmentation.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

@@ -0,0 +1,6 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="" vcs="Git" />
+  </component>
+</project>

app.py

@@ -0,0 +1,47 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+#load all models at the start
+unet_path = hf_hub_download(repo_id="treephones/tool-seg-unet", filename="1_simple_unet.keras")
+resnet_path = hf_hub_download(repo_id="treephones/tool-seg-resnet50-unet", filename="2_resnet50_unet.keras")
+fcn_path = hf_hub_download(repo_id="treephones/tool-seg-fcn-8s", filename="3_fcn_8s.keras")
+
+unet = tf.keras.models.load_model(unet_path, compile=False)
+rn50_unet = tf.keras.models.load_model(resnet_path, compile=False)
+fcn_8s = tf.keras.models.load_model(fcn_path, compile=False)
+#preprocess
+def preprocess_image(img: Image.Image):
+    img = img.convert("RGB").resize((256, 256))
+    img = np.array(img).astype(np.float32) / 255.0
+    return np.expand_dims(img, axis=0)
+
+#predict
+def predict_all_models(img):
+    tensor = preprocess_image(img)
+
+    out1 = unet.predict(tensor)[0]
+    out2 = rn50_unet.predict(tensor)[0]
+    out3 = fcn_8s.predict(tensor)[0]
+
+    out1_img = Image.fromarray((out1 * 255).astype(np.uint8))
+    out2_img = Image.fromarray((out2 * 255).astype(np.uint8))
+    out3_img = Image.fromarray((out3 * 255).astype(np.uint8))
+
+    return out1_img, out2_img, out3_img
+
+#gradio stuff
+demo = gr.Interface(
+    fn=predict_all_models,
+    inputs=gr.Image(label="Upload an Image", type="pil"),
+    outputs=[
+        gr.Image(label="Simple U-Net Output"),
+        gr.Image(label="ResNet50 + U-Net Output"),
+        gr.Image(label="FCN-8s Output")
+    ],
+    title="Tool Segmentation Comparison with Multiple Models",
+    description="Upload a single image to see how each segmentation model performs."
+)
+
+demo.launch()

requirements.txt

@@ -0,0 +1,5 @@
+gradio
+tensorflow
+numpy
+pillow
+huggingface_hub