fix diffusers 0.4.0

.dockerignore

@@ -2,4 +2,5 @@ src/stable-diffusion-streamlit/pages/model/result
 src/stable-diffusion-streamlit/pages/model/onnx
 __pycache__
 docker/.env
-tag.sh
+tag.sh
+docker/volume

.gitignore

@@ -2,4 +2,5 @@ result
 onnx
 __pycache__
 docker/.env
-tag.sh
+tag.sh
+docker/volume

docker/docker-compose.yaml

@@ -0,0 +1,15 @@
+version: "2.3"
+services:
+  stable-diffusion-streamlit-onnxquantized:
+    container_name: stable-diffusion-streamlit-onnxquantized
+    image: lowinli98/stable-diffusion-streamlit-onnxquantized:v0.1
+    expose:
+      - 8501
+    ports:
+      - "8501:8501"
+    environment:
+      - APP_TITLE=Stable Diffusion Streamlit
+    restart: always
+    volumes:
+      - /etc/localtime:/etc/localtime
+      - ./volume:/app/pages/model/result

docker/requirements.txt

@@ -2,8 +2,6 @@ ftfy==6.1.1
 onnx==1.12.0
 onnxruntime==1.12.1
 streamlit==1.13.0
-streamlit-image-comparison==0.0.2
 transformers==4.22.2
 diffusers==0.4.0
-torch==1.10.0+cpu
-pandas==1.4.1
+torch==1.10.0+cpu

src/stable-diffusion-streamlit/pages/model/inference.py

@@ -3,8 +3,14 @@
 import json
 
 root = os.getcwd()
-
-if root[-3:] == "src":
+last_dir = os.path.split(root)[-1]
+if last_dir == "stable-diffusion-streamlit":
+    model_dir = os.path.join(root, "pages/model/onnx")
+    result_dir = os.path.join(root, "pages/model/result")
+elif last_dir == "pages":
+    model_dir = os.path.join(root, "model/onnx")
+    result_dir = os.path.join(root, "model/result")
+elif last_dir == "app":
     model_dir = os.path.join(root, "pages/model/onnx")
     result_dir = os.path.join(root, "pages/model/result")
 else:

src/stable-diffusion-streamlit/pages/model/quantization.py

@@ -4,23 +4,24 @@
 
 def quant():
     for root, dirs, filenames in os.walk("./onnx"):
-        for filename in filenames:
-            if "model.onnx" in filenames:
-                if "weights.pb" in filenames:
-                    external_data = True
-                else:
-                    external_data = False
-                quantize_dynamic(
-                    model_input=os.path.join(root, "model.onnx"),
-                    model_output=os.path.join(root, "model.onnx"),  # 量化后直接覆盖原onnx文件
-                    per_channel=True,
-                    reduce_range=True,
-                    weight_type=QuantType.QUInt8,
-                    optimize_model=True,
-                    use_external_data_format=external_data,
-                )
-                print("Quantized model saved at: ", os.path.join(root, "model.onnx"))
-
+        if "model.onnx" in filenames:
+            if "weights.pb" in filenames:
+                external_data = True
+            else:
+                external_data = False
+            quantize_dynamic(
+                model_input=os.path.join(root, "model.onnx"),
+                model_output=os.path.join(root, "model.onnx"),  # 量化后直接覆盖原onnx文件
+                per_channel=True,
+                reduce_range=True,
+                weight_type=QuantType.QUInt8,
+                optimize_model=True,
+                use_external_data_format=external_data,
+            )
+            print("Quantized model saved at: ", os.path.join(root, "model.onnx"))
+            if "weights.pb" in filenames:
+                os.remove(os.path.join(root, "weights.pb"))
+                print("Removed weights.pb")
 
 if __name__ == "__main__":
     quant()

src/stable-diffusion-streamlit/pages/文字转图片.py

@@ -1,5 +1,4 @@
 import streamlit as st
-import pandas as pd
 import numpy as np
 import time
 import threading
@@ -25,15 +24,6 @@
     ce, c1, ce, c2, c3 = st.columns([0.07, 1, 0.07, 5, 0.07])
     with c1:
         st.subheader("参数配置", anchor=None)
-        guidance_scale = st.slider(
-            "指导参数(guidance_scale)",
-            min_value=0.0,
-            max_value=30.0,
-            value=7.0,
-            step=0.1,
-            help="值越大，约接近输入文字 \n Defined in https://arxiv.org/abs/2207.12598 \n Guidance scale is enabled by setting `guidance_scale > 1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`, usually at the expense of lower image quality.",
-            label_visibility="visible",
-        )
         num_inference_steps = st.slider(
             "生成轮数(num_inference_steps)",
             min_value=5,
@@ -43,6 +33,15 @@
             label_visibility="visible",
             help="约大生成图片质量越高，但是速度越慢 \n The number of denoising steps. More denoising steps usually lead to a higher quality image at the expense of slower inference.",
         )
+        guidance_scale = st.slider(
+            "指导参数(guidance_scale)",
+            min_value=0.0,
+            max_value=30.0,
+            value=7.0,
+            step=0.1,
+            help="值越大，约接近输入文字 \n Defined in https://arxiv.org/abs/2207.12598 \n Guidance scale is enabled by setting `guidance_scale > 1`. Higher guidance scale encourages to generate images that are closely linked to the text `prompt`, usually at the expense of lower image quality.",
+            label_visibility="visible",
+        )
         height = st.slider(
             "高度像素(height)",
             min_value=64,
@@ -86,6 +85,14 @@
             disabled=False,
             label_visibility="visible",
         )
+        negative_prompt = st.text_area(
+            "输入不要生成的文字描述，不填为不使用",
+            value="",
+            help="The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored if `guidance_scale` is less than `1`).",
+            disabled=False,
+            label_visibility="visible",
+        )
+        negative_prompt = None
         submit_button = st.form_submit_button("开始生成", help=None, args=None, kwargs=None)
         my_bar = st.progress(0)
         if not submit_button:
@@ -98,8 +105,8 @@
             width,
             num_inference_steps,
             guidance_scale,
-            eta,
-            None,
+            negative_prompt,
+            eta
         )
         t = PipelineThread(func=quant_pipe, args=args)
         t.start()
@@ -110,7 +117,7 @@
             else:
                 counter = 0
             progress = min(
-                t.func.scheduler.counter / (t.func.scheduler.num_inference_steps + 1),
+                t.func.scheduler.counter / (num_inference_steps + 1),
                 1.0,
             )
             my_bar.progress(progress)

src/stable-diffusion-streamlit/pages/画廊.py

@@ -2,26 +2,28 @@
 import os
 import json
 
-tab1, tab2 = st.tabs(["文字转图片"])
+# tab1 = st.tabs(["文字转图片"])
 
-with tab1:
-    list_uid = os.listdir("pages/model/result/text2image")
-    list_uid = sorted(list_uid, reverse=True)
+# with tab1:
+result_dir = "pages/model/result/text2image"
+os.makedirs(result_dir, exist_ok=True)
+list_uid = os.listdir(result_dir)
+list_uid = sorted(list_uid, reverse=True)
 
-    for uid in list_uid:
-        try:
-            with open(
-                os.path.join("pages/model/result/text2image", uid, "config.json"), "r"
-            ) as f:
-                config = json.load(f)
+for uid in list_uid:
+    try:
+        with open(
+            os.path.join(result_dir, uid, "config.json"), "r"
+        ) as f:
+            config = json.load(f)
 
-            with st.container():
-                st.caption(uid)
-                st.image(
-                    f"pages/model/result/text2image/{uid}/image.png",
-                    caption=str(config["text_prompt"]),
-                )
-                st.json(config, expanded=False)
-            st.markdown("---")
-        except:
-            pass
+        with st.container():
+            st.caption(uid)
+            st.image(
+                os.path.join(result_dir, uid, "image.png"),
+                caption=str(config["text_prompt"]),
+            )
+            st.json(config, expanded=False)
+        st.markdown("---")
+    except:
+        pass