102 lines
3.0 KiB
Python
102 lines
3.0 KiB
Python
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from PIL import Image
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from sanic import Sanic
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from sanic.response import json as json_answer
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import numpy as np
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from tensorflow import keras
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from tensorflow.keras.utils import img_to_array
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import io
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import os
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import json
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import requests
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os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
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app = Sanic("Ai")
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model_name = "../beerd_imagenet_25_04_2023.keras"
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test_model_imagenet = keras.models.load_model(model_name)
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model_name = "../beerd_25_04_2023.keras"
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test_model = keras.models.load_model(model_name)
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dict_names = {}
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with open("beerds.json", "r") as f:
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dict_names = json.loads(f.read())
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for key in dict_names:
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dict_names[key] = dict_names[key].replace("_", " ")
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app.static("/", "index.html", name="main")
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app.static("/static/", "static/", name="static")
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VK_URL = "https://api.vk.com/method/"
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TOKEN = "vk1.a.2VJFQn9oTIqfpVNcgk7OvxXU8TZPomCH4biRvZEZp8-tQTi8IdKajlXCY5vJbLFjjPGrRWpsM8wbG1mek2pVpktwqi1MGAFJQfQafg68buH7YiE3GtClgWhZNuDUX5PwQuANLRVh6Ao-DcN0Z-72AmWmsIKhf9A4yuE8q3O6Asn_miGvO9gUY_JpctKEVtAYIEhbJtQK7hxW8qpud8J5Vg"
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headers = {"Authorization": f"Bearer {TOKEN}"}
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group_id = 220240483
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postfix = "?v=5.131"
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IMAGES = {}
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def get_images():
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global IMAGES
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r = requests.get(
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f"{VK_URL}photos.getAll{postfix}&access_token={TOKEN}&owner_id=-{group_id}&count=200")
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items = r.json().get("response").get("items")
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for item in items:
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for s in item.get("sizes"):
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if s.get("type") != "x":
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continue
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IMAGES[item.get("text")] = s.get("url")
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break
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get_images()
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@app.post("/beeds")
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async def beeds(request):
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body = request.files.get("f").body
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img = Image.open(io.BytesIO(body))
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img = img.convert('RGB')
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img_net = img.resize((180, 180, ), Image.BILINEAR)
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img_array = img_to_array(img_net)
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test_loss_image_net = test_model_imagenet.predict(
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np.expand_dims(img_array, 0))
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img = img.resize((200, 200, ), Image.BILINEAR)
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img_array = img_to_array(img)
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test_loss = test_model.predict(np.expand_dims(img_array, 0))
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result = {}
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for i, val in enumerate(test_loss[0]):
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if val <= 0.09:
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continue
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result[val] = dict_names[str(i)]
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result_net = {}
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for i, val in enumerate(test_loss_image_net[0]):
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if val <= 0.09:
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continue
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result_net[val] = dict_names[str(i)]
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items_one = dict(sorted(result.items(), reverse=True))
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items_two = dict(sorted(result_net.items(), reverse=True))
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images = []
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for item in items_one:
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name = items_one[item].replace("_", " ")
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if name not in IMAGES:
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continue
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images.append({"name": name, "url": IMAGES[name]})
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for item in items_two:
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name = items_two[item].replace("_", " ")
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if name not in IMAGES:
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continue
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images.append({"name": name, "url": IMAGES[name]})
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return json_answer({
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"results": items_one,
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"results_net": items_two,
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"images": images,
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})
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if __name__ == "__main__":
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app.run(auto_reload=True, port=4003, host="0.0.0.0")
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