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+* text=auto

.gitignore

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+# Byte-compiled / optimized / DLL files
+__pycache__/
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+*$py.class
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+# PyBuilder
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+# Jupyter Notebook
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+.space
+.onnx
+model.onnx

README.md

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+# GAN-API
+
+http://gan-230522.eddy3d.com/test
+ 

api.py

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+from fastapi import FastAPI, File, UploadFile, responses
+from PIL import Image
+import io
+import numpy as np
+import onnxruntime as rt
+
+app = FastAPI()
+
+sess = rt.InferenceSession("model.onnx")
+
+@app.get("/test")
+async def test():
+    return {"message": "API is working"}
+
+@app.api_route("/dummy", methods=["POST"])
+async def dummy_function(file: UploadFile = File(...)):
+    print("Dummy function called")
+    # Perform some dummy processing or return a dummy response
+    return {"message": "Dummy function called"}
+
+#@app.api_route("/process_image", methods=["POST"])
+@app.post("/process_image")
+async def process_image(file: UploadFile = File(...)):
+    input_data = await file.read()
+    input_image = Image.open(io.BytesIO(input_data)).convert("RGB")
+
+    # Resize and convert to numpy array
+    input_array = np.array(input_image.resize((512, 512)))
+
+    # Normalize to [-1, 1]
+    input_array = (input_array.astype(np.float32) / 127.5) - 1
+    input_array = np.expand_dims(input_array, axis=0)
+
+    # Reorder dimensions to match model's expectations
+    input_array = input_array.transpose((0, 3, 1, 2))  # Move the color dimension to the correct position
+
+    inputs = {sess.get_inputs()[0].name: input_array}
+    outputs = sess.run(None, inputs)
+
+    # Denormalize from [-1, 1] to [0, 255]
+    output_array = (outputs[0][0].transpose((1, 2, 0)) + 1) * 127.5
+    output_array = np.clip(output_array, 0, 255)  # Clip values outside of valid range
+
+    # Convert back to image
+    output_image = Image.fromarray(output_array.astype(np.uint8), "RGB")
+
+    byte_arr = io.BytesIO()
+    output_image.save(byte_arr, format='PNG')
+    byte_arr.seek(0)  # Move cursor to the beginning of the file
+
+    return responses.StreamingResponse(byte_arr, media_type="image/png")

requirements.txt

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+fastapi
+uvicorn[standard]
+python-multipart 
+uvicorn 
+onnxruntime 
+pillow 
+numpy
+requests

test.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import requests\n",
+    "from PIL import Image\n",
+    "import io\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "b'{\"message\":\"API is working\"}'\n"
+     ]
+    }
+   ],
+   "source": [
+    "response = requests.get(\"http://gan-230522.eddy3d.com/test\")\n",
+    "\n",
+    "print(response.content)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Open your image file in binary mode\n",
+    "with open(\"test_input.png\", \"rb\") as f:\n",
+    "    img_binary = f.read()\n",
+    "\n",
+    "\n",
+    "# Create a file-like object from the image binary data\n",
+    "img_file = io.BytesIO(img_binary)\n",
+    "\n",
+    "# Open the image using PIL\n",
+    "img_in = Image.open(img_file)\n",
+    "\n",
+    "# Display the image\n",
+    "img_in.show()\n",
+    "\n",
+    "\n",
+    "# Send the POST request\n",
+    "# response = requests.post('http://127.0.0.1:8000/process_image', files={'file': img_binary})\n",
+    "response = requests.post(\n",
+    "    \"https://gan-230522.eddy3d.com/process_image\", files={\"file\": img_binary}\n",
+    ")\n",
+    "\n",
+    "\n",
+    "# The response is an image file, so we need to convert it back to an image\n",
+    "image = Image.open(io.BytesIO(response.content))\n",
+    "\n",
+    "# Now you can display the image or save it to a file\n",
+    "image.show()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "b'{\"message\":\"API is working\"}'\n"
+     ]
+    }
+   ],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "ganapi",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}