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Update app.py
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app.py
CHANGED
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@@ -5,6 +5,7 @@ from fastapi import FastAPI
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from pydantic import BaseModel
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from collections import defaultdict
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import uvicorn
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import os
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app = FastAPI()
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@@ -12,12 +13,11 @@ app = FastAPI()
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class InputData(BaseModel):
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image_base64: str
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def save_base64_image_cv(base64_str, output_path
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image_data = base64.b64decode(base64_str)
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nparr = np.frombuffer(image_data, np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
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# jika RGBA → tempelkan ke background putih
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if img is not None and img.shape[2] == 4:
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alpha = img[:, :, 3] / 255.0
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rgb = img[:, :, :3]
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@@ -25,9 +25,8 @@ def save_base64_image_cv(base64_str, output_path="final.png"):
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img = (rgb * alpha[:, :, None] + white_bg * (1 - alpha[:, :, None])).astype(np.uint8)
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cv2.imwrite(output_path, img)
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return output_path
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def extract_icon_positions(image_path
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img = cv2.imread(image_path)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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@@ -69,29 +68,36 @@ def find_rarest_icon_position(icon_features, positions):
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rarest_group = min(groups.values(), key=len)
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idx = rarest_group[0]
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return positions[idx][0], positions[idx][1]
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@app.post("/predict")
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async def predict(data: InputData):
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try:
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save_base64_image_cv(data.image_base64,
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icon_features, positions = extract_icon_positions(
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if not positions:
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return {"error": "No icons detected"}
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x, y = find_rarest_icon_position(icon_features, positions)
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except Exception as e:
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return {"error": str(e)}
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=7860)
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from pydantic import BaseModel
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from collections import defaultdict
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import uvicorn
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import uuid
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import os
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app = FastAPI()
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class InputData(BaseModel):
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image_base64: str
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def save_base64_image_cv(base64_str, output_path):
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image_data = base64.b64decode(base64_str)
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nparr = np.frombuffer(image_data, np.uint8)
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img = cv2.imdecode(nparr, cv2.IMREAD_UNCHANGED)
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if img is not None and img.shape[2] == 4:
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alpha = img[:, :, 3] / 255.0
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rgb = img[:, :, :3]
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img = (rgb * alpha[:, :, None] + white_bg * (1 - alpha[:, :, None])).astype(np.uint8)
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cv2.imwrite(output_path, img)
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def extract_icon_positions(image_path):
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img = cv2.imread(image_path)
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gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
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rarest_group = min(groups.values(), key=len)
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idx = rarest_group[0]
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return positions[idx][0], positions[idx][1]
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@app.post("/predict")
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async def predict(data: InputData):
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# file unik → aman untuk paralel
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tmp_file = f"{uuid.uuid4().hex}.png"
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try:
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save_base64_image_cv(data.image_base64, tmp_file)
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icon_features, positions = extract_icon_positions(tmp_file)
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if not positions:
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return {"error": "No icons detected"}
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x, y = find_rarest_icon_position(icon_features, positions)
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return {
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"x": x,
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"y": y,
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"count": len(positions) # opsional
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}
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except Exception as e:
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return {"error": str(e)}
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finally:
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if os.path.exists(tmp_file):
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os.remove(tmp_file)
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=7860)
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