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from fastapi import FastAPI ,Request ,Form, UploadFile, File |
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from fastapi.responses import JSONResponse |
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from fastapi.responses import HTMLResponse, FileResponse |
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import os |
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import io |
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from PIL import ImageOps,Image ,ImageFilter |
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import matplotlib.pyplot as plt |
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import numpy as np |
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import ast |
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import server |
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app = FastAPI() |
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@app.get('/') |
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def main(): |
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return "Hello World taha" |
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@app.post('/predict') |
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async def predict(supported_types_str: str = Form(),age: str = Form() , file: UploadFile = File(...)): |
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supported_types=ast.literal_eval(supported_types_str) |
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contents = await file.read() |
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image = Image.open(io.BytesIO(contents)) |
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processed_image = image.convert("L") |
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output_file_path = "tmp_processed_image.png" |
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processed_image.save(output_file_path) |
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return FileResponse(output_file_path, media_type='image/png', filename="tmp_processed_image.png") |
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@app.post('/predict2') |
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async def predict2(supported_types_str: str = Form(...), age: str = Form(...), file: UploadFile = File(...)): |
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contents = await file.read() |
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image = Image.open(io.BytesIO(contents)) |
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processed_image = image.convert("L") |
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img_byte_arr = io.BytesIO() |
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processed_image.save(img_byte_arr, format='PNG') |
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img_byte_arr.seek(0) |
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html_content = f""" |
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<html> |
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<body> |
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<h3>Processed Image:</h3> |
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<img src="data:image/png;base64,{img_byte_arr.getvalue().decode('latin1')}" alt="Processed Image" style="max-width: 500px;"/> |
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<br><br> |
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<p>Your name: {supported_types_str}</p> |
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<p>Your age: {age}</p> |
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<p><a href="/download">Download Processed Image</a></p> |
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</body> |
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</html> |
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""" |
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return HTMLResponse(content=html_content) |
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