Stuff

.gitignore

@@ -1,2 +1,6 @@
 *.jpeg
 *.jpg
+*.png
+imageserver/images/
+imageserver/models
+__pycache__

imageserver/client.py

@@ -0,0 +1,40 @@
+# import aiohttp
+# import aiofiles
+import asyncio
+import requests
+from io import BytesIO
+from PIL import Image
+import shutil
+from random import randint
+
+def main():
+    print("Starting")
+
+    img = Image.new('RGB', (25, 25), color = (randint(0, 255), randint(0, 255), randint(0, 255)))
+    img = Image.open("/home/jimmy/image.png")
+    byte_io = BytesIO()
+    img.save(byte_io, 'png')
+    byte_io.seek(0)
+
+    r = requests.post(url='http://localhost:8000?text=cartoon',
+        files={
+            'my_file': (
+                '1.png',
+                byte_io,
+                'image/png'
+            ),
+        },
+        stream=True
+    )
+    print(r.status_code)
+
+    if r.status_code == 200:
+        byte_io = BytesIO(r.content)
+        img = Image.open(byte_io)
+        img.show()
+
+if __name__ == '__main__':
+    main()
+
+
+

imageserver/main.py

@@ -14,8 +14,8 @@ from PIL import Image
 
 load_dotenv()
 
-# pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", num_inference_steps=100, revision="fp16", torch_dtype=torch.float16, use_auth_token=getenv("TOKEN"))
-# pipe.to("cuda")
+pipe = StableDiffusionImg2ImgPipeline.from_pretrained("CompVis/stable-diffusion-v1-4", num_inference_steps=100, revision="fp16", torch_dtype=torch.float16, use_auth_token=getenv("TOKEN"))
+pipe.to("cuda")
 
 class Text(BaseModel):
     text: str
@@ -25,39 +25,44 @@ class Text(BaseModel):
 app = FastAPI()
 
 @app.post("/",
-    # responses = {
-    #     200: {
-    #         "content": {"image/png": {}}
-    #     }
-    # },
-    # response_class=Response
+    responses = {
+        200: {
+            "content": {"image/png": {}}
+        }
+    },
+    response_class=Response
 )
-def root(text: str):
+async def root(text: str, my_file: UploadFile = File(...)):
     prompt = text.replace('+', ' ')
     print(prompt)
-    #request_object_content = file.read()
-    # img = Image.open(io.BytesIO(request_object_content))
+    request_object_content = await my_file.read()
+    img = Image.open(io.BytesIO(request_object_content))
+
+    height_orig = img.height
+    width_orig = img.width
+    aspect_ratio = width_orig / height_orig 
+    width_new = 512
+    height_new = int(width_new / aspect_ratio)
+    img = img.resize((width_new, height_new), 0)
+    try:  
+        resp = pipe(prompt, image=img)
+        print(resp)
+        image = resp.images[0]
+    except RuntimeError as e:
+        print(e)
+        raise HTTPException(status_code=202, detail="Busy")
+    except Exception as e:
+        raise HTTPException(status_code=504, detail=str(e)) 
+    if resp["nsfw_content_detected"] == [True]:
+        raise HTTPException(status_code=418, detail="NSFW")
+    
+    imgByteArr = io.BytesIO()
+    image.save(imgByteArr, format="PNG")
+    imgByteArr = imgByteArr.getvalue()
+    running = False
+    return Response(content=imgByteArr, media_type="image/png")
+    
 
-    # height_orig = img.height
-    # width_orig = img.width
-    # aspect_ratio = width_orig / height_orig 
-    # width_new = 512
-    # height_new = int(width_new / aspect_ratio)
-    # img = img.resize((width_new, height_new), 0)
 
-    # try:
 
-    #     resp = pipe(prompt,  init_image=img)
-    #     print(resp)
-    #     image = resp.images[0]
-    # except RuntimeError as e:
-    #     print(e)
-    #     raise HTTPException(status_code=202, detail="Busy")
-    # except:
-    #     raise HTTPException(status_code=504) 
 
-    # imgByteArr = io.BytesIO()
-    # image.save(imgByteArr, format="PNG")
-    # imgByteArr = imgByteArr.getvalue()
-    # running = False
-    # return Response(content=imgByteArr, media_type="image/png")

pi.py

@@ -4,19 +4,33 @@ import cv2
 from gpiozero import LED, Button
 from picamera2 import Picamera2
 from time import sleep
+import asyncio
+import requests
+from io import BytesIO
+from PIL import Image
+import shutil
+from random import randint
+import numpy as np
+import sys
+import pyautogui
 
 red = LED(19)
 blue = LED(26)
 green = LED(13)
 button = Button(5)
+button2 = Button(2)
+button3 = Button(3)
+
 
 # Grab images as numpy arrays and leave everything else to OpenCV.
-x = 1920
-y = 1080
+x = 512
+y = 512
+
+
+print(pyautogui.size())
+
+x, y = pyautogui.size()
 
-cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
-#cv2.setWindowProperty("window",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
-cv2.resizeWindow("window", x, y)
 picam2 = Picamera2()
 
 capture_config = picam2.create_preview_configuration(main={"size": (x, y),
@@ -24,25 +38,69 @@ capture_config = picam2.create_preview_configuration(main={"size": (x, y),
 picam2.configure(capture_config)
 picam2.start()
 
+cv2.namedWindow("window", cv2.WND_PROP_FULLSCREEN)
+# cv2.setWindowProperty("window",cv2.WND_PROP_FULLSCREEN,cv2.WINDOW_FULLSCREEN)
 while True:
+    
+    # cv2.resizeWindow("window", x, y)
     while True:
         im = picam2.capture_array()
 
 
         cv2.imshow("window", im)
-        if cv2.waitKey(40) & 0xFF == ord('a') or button.value:
+        if cv2.waitKey(40) & 0xFF == ord('q'):
+            sys.exit()
+        if button2.value: 
             break
 
     while button.value:
         pass
 
-    while not button.value:
-        sleep(0.1)
+    color_converted = cv2.cvtColor(im, cv2.COLOR_BGR2RGB)
+    img=Image.fromarray(color_converted)
 
-    while not button.value:
-        pass
+    byte_io = BytesIO()
+    img.save(byte_io, 'png')
+    byte_io.seek(0)
+
+    print("-------------------Generating Image----------------------")
+    r = requests.post(url='http://192.168.1.100:8000?text=into cyborg robot ',
+        files={
+            'my_file': (
+                '1.png',
+                byte_io,
+                'image/png'
+            ),
+        },
+        stream=True
+    )
+    print(r.status_code)
+
+    if r.status_code == 200:
+        byte_io = BytesIO(r.content)
+        img = Image.open(byte_io)
+   
+        # img.show()
+        height_orig = img.height
+        width_orig = img.width
+        aspect_ratio = width_orig / height_orig 
+        width_new = x
+        height_new = int(width_new / aspect_ratio)
+        img = img.resize((width_new, height_new), 0)
+
+        numpy_image=np.array(img) 
+        opencv_image=cv2.cvtColor(numpy_image, cv2.COLOR_RGB2BGR) 
+      
+        cv2.imshow("window", opencv_image)
+        print("---------------------------------Image Generated-----------------------------")
+
+ 
+    
+    
+    print("--------------------Sleeping-------------------------")
+    sleep(10)
+    print("--------------------Slept----------------------------")
 
-    sleep(1)