rm wrongly uploaded folder (#24)

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KevinHuSh 2024-01-15 19:51:48 +08:00 committed by GitHub
parent 3198faf2d2
commit 3859fce6bf
7 changed files with 0 additions and 118 deletions

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FROM ubuntu:22.04 as base
RUN apt-get update
ENV TZ="Asia/Taipei"
RUN apt-get install -yq \
build-essential \
curl \
libncursesw5-dev \
libssl-dev \
libsqlite3-dev \
libgdbm-dev \
libc6-dev \
libbz2-dev \
software-properties-common \
python3.11 python3.11-dev python3-pip
RUN apt-get install -yq git
RUN pip3 config set global.index-url https://mirror.baidu.com/pypi/simple
RUN pip3 config set global.trusted-host mirror.baidu.com
RUN pip3 install --upgrade pip
RUN pip3 install torch==2.0.1
RUN pip3 install torch-model-archiver==0.8.2
RUN pip3 install torchvision==0.15.2
COPY requirements.txt .
WORKDIR /docgpt
ENV PYTHONPATH=/docgpt/

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from abc import ABC
from openai import OpenAI
import os
import base64
from io import BytesIO
class Base(ABC):
def describe(self, image, max_tokens=300):
raise NotImplementedError("Please implement encode method!")
class GptV4(Base):
def __init__(self):
import openapi
openapi.api_key = os.environ["OPENAPI_KEY"]
self.client = OpenAI()
def describe(self, image, max_tokens=300):
buffered = BytesIO()
try:
image.save(buffered, format="JPEG")
except Exception as e:
image.save(buffered, format="PNG")
b64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
res = self.client.chat.completions.create(
model="gpt-4-vision-preview",
messages=[
{
"role": "user",
"content": [
{
"type": "text",
"text": "请用中文详细描述一下图中的内容,比如时间,地点,人物,事情,人物心情等。",
},
{
"type": "image_url",
"image_url": {
"url": f"data:image/jpeg;base64,{b64}"
},
},
],
}
],
max_tokens=max_tokens,
)
return res.choices[0].message.content.strip()
class QWen(Base):
def chat(self, system, history, gen_conf):
from http import HTTPStatus
from dashscope import Generation
from dashscope.api_entities.dashscope_response import Role
# export DASHSCOPE_API_KEY=YOUR_DASHSCOPE_API_KEY
response = Generation.call(
Generation.Models.qwen_turbo,
messages=messages,
result_format='message'
)
if response.status_code == HTTPStatus.OK:
return response.output.choices[0]['message']['content']
return response.message

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Fetching 6 files: 0%| | 0/6 [00:00<?, ?it/s] Fetching 6 files: 100%|██████████| 6/6 [00:00<00:00, 106184.91it/s]
----------- Model Configuration -----------
Model Arch: GFL
Transform Order:
--transform op: Resize
--transform op: NormalizeImage
--transform op: Permute
--transform op: PadStride
--------------------------------------------
Could not find image processor class in the image processor config or the model config. Loading based on pattern matching with the model's feature extractor configuration.
The `max_size` parameter is deprecated and will be removed in v4.26. Please specify in `size['longest_edge'] instead`.
Some weights of the model checkpoint at microsoft/table-transformer-structure-recognition were not used when initializing TableTransformerForObjectDetection: ['model.backbone.conv_encoder.model.layer3.0.downsample.1.num_batches_tracked', 'model.backbone.conv_encoder.model.layer2.0.downsample.1.num_batches_tracked', 'model.backbone.conv_encoder.model.layer4.0.downsample.1.num_batches_tracked']
- This IS expected if you are initializing TableTransformerForObjectDetection from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing TableTransformerForObjectDetection from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
WARNING:root:The files are stored in /opt/home/kevinhu/docgpt/, please check it!