first

.gitignore

@@ -0,0 +1 @@
+./flagged

.vscode/settings.json

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+{
+    "[python]": {
+        "editor.defaultFormatter": "ms-python.black-formatter"
+    },
+    "python.formatting.provider": "none"
+}

Pipfile

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+[[source]]
+url = "https://pypi.org/simple"
+verify_ssl = true
+name = "pypi"
+
+[packages]
+gradio = "==3.35.2"
+numpy = "==1.23.3"
+tensorflow = "==2.12.0"
+
+[dev-packages]
+
+[requires]
+python_version = "3.11"

README.md

@@ -1,10 +1,10 @@
 ---
-title: Fishv2
-emoji: 😻
-colorFrom: indigo
+title: Fish
+emoji: 🚀
+colorFrom: yellow
 colorTo: gray
 sdk: gradio
-sdk_version: 3.35.2
+sdk_version: 3.4.1
 app_file: app.py
 pinned: false
 ---

app.py

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+import gradio as gr
+from huggingface_hub import from_pretrained_keras
+from tensorflow.keras.preprocessing.image import load_img
+from tensorflow.keras.preprocessing.image import img_to_array
+from tensorflow.keras.preprocessing import image
+import numpy as np
+
+model = from_pretrained_keras("yusyel/fishv2")
+
+
+class_names = [
+    "Black Sea Sprat",
+    "Gilt-Head Bream",
+    "Hourse Mackerel",
+    "Red Sea Bream",
+    "Red Mullet",
+    "Sea Bass",
+    "Shrimp",
+    "Striped Red Mullet",
+    "Trout",
+]
+
+
+def preprocess_image(img, label):
+    img = load_img(img, target_size=(199, 199))
+    img = image.img_to_array(img)
+    img = np.expand_dims(img, axis=0)
+    img /= 255.0
+    print(img.shape)
+    return img, label
+
+
+
+def predict(img):
+    img, _ = preprocess_image(img, 1)
+    pred = model.predict(img)
+    pred = np.squeeze(pred).astype(float)
+    print(pred)
+    return dict(zip(class_names, pred))
+
+
+demo = gr.Interface(
+    fn=predict,
+    inputs=[gr.inputs.Image(type="filepath")],
+    outputs=gr.outputs.Label(),
+    examples=[
+        ["./img/Black_Sea_Sprat.png"],
+        ["./img/Gilt_Head_Bream.JPG"],
+        ["./img/Horse_Mackerel.png"],
+        ["./img/Red_mullet.png"],
+        ["./img/Red_Sea_Bream.JPG"],
+        ["./img/Sea_Bass.JPG"],
+        ["./img/Shrimp.png"],
+        ["./img/Striped_Red_Mullet.png"],
+        ["./img/Trout.png"],
+    ],
+    title="lorem ipsun",
+    description="kljflksjdlkfjksd",
+)
+
+demo.launch()

requirements.txt

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+gradio==3.35.2
+numpy==1.23.3
+tensorflow==2.12.0