Update main.py
Browse files
main.py
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@@ -6,7 +6,7 @@ from io import BytesIO
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app = FastAPI()
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# গুগল-এর
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classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
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@app.get("/")
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@@ -16,31 +16,20 @@ def read_root():
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@app.get("/analyze")
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def analyze(url: str):
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try:
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#
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img = Image.open(BytesIO(res.content)).convert("RGB")
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# AI Processing
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results = classifier(img)
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# Confidence Check (85% = 0.85)
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top_score = results[0]['score']
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if top_score >= 0.85:
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return {
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"success": True,
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"confidence": f"High ({int(top_score*100)}%)",
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"names": [results[0]['label'].title()]
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}
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else:
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# যদি এআই পুরোপুরি নিশ্চিত না হয়, তবে সম্ভাব্য সেরা ৩টি নাম দেবে
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top_3 = [r['label'].title() for r in results[:3]]
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return {
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"success": True,
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"confidence": "Low",
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"names": top_3
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}
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except Exception as e:
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return {"success": False, "error": str(e)}
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app = FastAPI()
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# গুগল-এর ভিশন এআই মডেল
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classifier = pipeline("image-classification", model="google/vit-base-patch16-224")
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@app.get("/")
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@app.get("/analyze")
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def analyze(url: str):
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try:
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# ব্রাউজার সেজে রিকোয়েস্ট পাঠানো যেন টিকটক ব্লক না করে
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headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64 AppleWebKit/537.36)"}
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res = requests.get(url, headers=headers, timeout=15)
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img = Image.open(BytesIO(res.content)).convert("RGB")
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# AI Processing
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results = classifier(img)
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top_score = results[0]['score']
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if top_score >= 0.85:
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return {"success": True, "confidence": f"High ({int(top_score*100)}%)", "names": [results[0]['label'].title()]}
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else:
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top_3 = [r['label'].title() for r in results[:3]]
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return {"success": True, "confidence": "Low", "names": top_3}
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except Exception as e:
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return {"success": False, "error": str(e)}
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