rm wrongly uploaded folder (#24)

python/Dockerfile

@@ -1,29 +0,0 @@
-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/
-

python/]

@@ -1,63 +0,0 @@
-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

python/res/1-0.tm

@@ -1,8 +0,0 @@
-2023-12-20 11:44:08.791336+00:00
-2023-12-20 11:44:08.853249+00:00
-2023-12-20 11:44:08.909933+00:00
-2023-12-21 00:47:09.996757+00:00
-2023-12-20 11:44:08.965855+00:00
-2023-12-20 11:44:09.011682+00:00
-2023-12-21 00:47:10.063326+00:00
-2023-12-20 11:44:09.069486+00:00

python/res/thumbnail-1-0.tm

@@ -1,3 +0,0 @@
-2023-12-27 08:21:49.309802+00:00
-2023-12-27 08:37:22.407772+00:00
-2023-12-27 08:59:18.845627+00:00

python/tmp.log

@@ -1,15 +0,0 @@
-
------------  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!