Create app.py

app.py

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+from transformers import AutoImageProcessor, AutoModelForImageClassification
+import torch
+from PIL import Image
+import gradio as gr
+
+# Загрузка модели
+model = AutoModelForImageClassification.from_pretrained("jeemsterri/fish_classification")
+processor = AutoImageProcessor.from_pretrained("jeemsterri/fish_classification")
+
+# Предсказание
+def classify_image(image):
+    inputs = processor(images=image, return_tensors="pt")
+    outputs = model(**inputs)
+    probs = torch.nn.functional.softmax(outputs.logits, dim=1)
+    confidence, predicted_class = torch.max(probs, dim=1)
+    label = model.config.id2label[predicted_class.item()]
+    return {label: float(confidence)}
+
+gr.Interface(fn=classify_image, 
+             inputs=gr.Image(type="pil"), 
+             outputs=gr.Label(num_top_classes=3),
+             title="Fish Species Classifier",
+             description="Upload a fish image and get the predicted species.").launch()