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app.py

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+import gradio as gr
+import gradio as gr
+import torch
+import torchvision.transforms as transforms
+from PIL import Image
+from torchvision import models
+
+# ข้อความ string ค่าของ classes ที่มี
+targets = ['Negative','Positive']
+
+# เตรียม data ก่อนเข้าโมเดล
+transform = transforms.Compose([
+    transforms.Resize(256),
+    transforms.CenterCrop(224),
+    transforms.ToTensor(),
+    transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
+])
+
+# ฟังก์ชันประมวลผลรูปภาพ
+def classify_image(img):
+    img = Image.fromarray(img.astype('uint8'), 'RGB')
+    img = transform(img).unsqueeze(0)
+    device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
+    img = img.to(device)
+
+    with torch.no_grad():
+        prediction = torch.nn.functional.softmax(model(img)[0], dim=0)
+        confidences = {targets[i]: float(prediction[i]) for i in range(2)}
+    return confidences
+
+# รันโปรแกรมเว็บ gradio
+demo = gr.Interface(fn=classify_image,
+             inputs=gr.Image(width=224, height=224),
+             outputs=gr.Label(num_top_classes=2),
+             examples=["examples/negative.jpeg", "examples/positive.jpeg"]) # ภาพตัวอย่างมาจาก folder examples
+
+demo.launch(share=True, debug=True)

model_blood.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:146d347cf6d13f3e7247132e72c4b1bb5690972afe129e0b5aa6d4ed7c17d824
+size 94395906