Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+dogs-vs-cats-model_transferlearning.keras filter=lfs diff=lfs merge=lfs -text
+images/dog1.jpeg filter=lfs diff=lfs merge=lfs -text
+pokemon-predict-model_transferlearning.keras filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,12 +1,6 @@
 ---
-title: Pokemon Deploy
-emoji: 🔥
-colorFrom: red
-colorTo: indigo
+title: pokemon-deploy
+app_file: pokemon-deploy.py
 sdk: gradio
 sdk_version: 4.27.0
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.ipynb

@@ -0,0 +1,252 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Requirement already satisfied: gradio in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (4.27.0)\n",
+      "Requirement already satisfied: huggingface-hub>=0.19.3 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from gradio) (0.22.2)\n",
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+      "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /Users/matis/Library/Python/3.10/lib/python/site-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio) (2.16.1)\n",
+      "Requirement already satisfied: exceptiongroup>=1.0.2 in /Users/matis/Library/Python/3.10/lib/python/site-packages (from anyio->httpx>=0.24.1->gradio) (1.1.3)\n",
+      "Requirement already satisfied: charset-normalizer<4,>=2 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from requests->huggingface-hub>=0.19.3->gradio) (3.3.0)\n",
+      "Requirement already satisfied: mdurl~=0.1 in /Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio) (0.1.2)\n",
+      "--- Logging error ---\n",
+      "Traceback (most recent call last):\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/utils/logging.py\", line 177, in emit\n",
+      "    self.console.print(renderable, overflow=\"ignore\", crop=False, style=style)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/rich/console.py\", line 1673, in print\n",
+      "    extend(render(renderable, render_options))\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/rich/console.py\", line 1305, in render\n",
+      "    for render_output in iter_render:\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/utils/logging.py\", line 134, in __rich_console__\n",
+      "    for line in lines:\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/rich/segment.py\", line 249, in split_lines\n",
+      "    for segment in segments:\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/rich/console.py\", line 1283, in render\n",
+      "    renderable = rich_cast(renderable)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_vendor/rich/protocol.py\", line 36, in rich_cast\n",
+      "    renderable = cast_method()\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/self_outdated_check.py\", line 130, in __rich__\n",
+      "    pip_cmd = get_best_invocation_for_this_pip()\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/utils/entrypoints.py\", line 58, in get_best_invocation_for_this_pip\n",
+      "    if found_executable and os.path.samefile(\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/genericpath.py\", line 101, in samefile\n",
+      "    s2 = os.stat(f2)\n",
+      "FileNotFoundError: [Errno 2] No such file or directory: '/Library/Frameworks/Python.framework/Versions/3.10/bin/pip'\n",
+      "Call stack:\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/runpy.py\", line 196, in _run_module_as_main\n",
+      "    return _run_code(code, main_globals, None,\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/runpy.py\", line 86, in _run_code\n",
+      "    exec(code, run_globals)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/__main__.py\", line 31, in <module>\n",
+      "    sys.exit(_main())\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/cli/main.py\", line 70, in main\n",
+      "    return command.main(cmd_args)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/cli/base_command.py\", line 101, in main\n",
+      "    return self._main(args)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/cli/base_command.py\", line 223, in _main\n",
+      "    self.handle_pip_version_check(options)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/cli/req_command.py\", line 190, in handle_pip_version_check\n",
+      "    pip_self_version_check(session, options)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/self_outdated_check.py\", line 236, in pip_self_version_check\n",
+      "    logger.warning(\"[present-rich] %s\", upgrade_prompt)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/logging/__init__.py\", line 1489, in warning\n",
+      "    self._log(WARNING, msg, args, **kwargs)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/logging/__init__.py\", line 1624, in _log\n",
+      "    self.handle(record)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/logging/__init__.py\", line 1634, in handle\n",
+      "    self.callHandlers(record)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/logging/__init__.py\", line 1696, in callHandlers\n",
+      "    hdlr.handle(record)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/logging/__init__.py\", line 968, in handle\n",
+      "    self.emit(record)\n",
+      "  File \"/Library/Frameworks/Python.framework/Versions/3.10/lib/python3.10/site-packages/pip/_internal/utils/logging.py\", line 179, in emit\n",
+      "    self.handleError(record)\n",
+      "Message: '[present-rich] %s'\n",
+      "Arguments: (UpgradePrompt(old='22.2.2', new='24.0'),)\n",
+      "Note: you may need to restart the kernel to use updated packages.\n"
+     ]
+    }
+   ],
+   "source": [
+    "%pip install gradio\n",
+    "import gradio as gr\n",
+    "import tensorflow as tf\n",
+    "import numpy as np\n",
+    "from PIL import Image"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model_path = \"pokemon-predict-model_transferlearning.keras\"\n",
+    "model = tf.keras.models.load_model(model_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Define the core prediction function\n",
+    "def predict_pokemon(image):\n",
+    "    # Preprocess image\n",
+    "    print(type(image))\n",
+    "    image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image\n",
+    "    image = image.resize((150, 150)) #resize the image to 150x150\n",
+    "    image = np.array(image)\n",
+    "    image = np.expand_dims(image, axis=0) # same as image[None, ...]\n",
+    "    \n",
+    "    # Predict\n",
+    "    prediction = model.predict(image)\n",
+    "    \n",
+    "    # Apply softmax to get probabilities for each class\n",
+    "    prediction = tf.nn.softmax(prediction)\n",
+    "    \n",
+    "    # Create a dictionary with the probabilities for each Pokemon\n",
+    "    evee = np.round(float(prediction[0][0]), 2)\n",
+    "    farfetched = np.round(float(prediction[0][1]), 2)\n",
+    "    graveler = np.round(float(prediction[0][2]), 2)\n",
+    "    venonta = np.round(float(prediction[0][3]), 2)\n",
+    "    \n",
+    "    return {'Evee': evee, 'Farfetched': farfetched, 'Graveler': graveler, 'Venonta': venonta}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Running on local URL:  http://127.0.0.1:7864\n",
+      "Running on public URL: https://625988e4933385a0d9.gradio.live\n",
+      "\n",
+      "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><iframe src=\"https://625988e4933385a0d9.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
+      ],
+      "text/plain": [
+       "<IPython.core.display.HTML object>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": []
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create the Gradio interface\n",
+    "input_image = gr.Image()\n",
+    "iface = gr.Interface(\n",
+    "    fn=predict_pokemon,\n",
+    "    inputs=input_image, \n",
+    "    outputs=gr.Label(),\n",
+    "    description=\"A simple mlp classification model for image classification using the mnist dataset.\")\n",
+    "iface.launch(share=True)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "venv_new",
+   "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": "3.10.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

dogs-vs-cats-model_transferlearning.keras

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b58a22c46ecaf95be00e5ea133d78d2126e0d7a15ff5afc9a49d537356519f6c
+size 250535603

flagged/log.csv

@@ -0,0 +1,2 @@
+image,output,flag,username,timestamp
+flagged/image/197e31f79189f1d3dc8c/cat3.jpeg,"{""label"": null, ""confidences"": null}",,,2024-04-20 18:14:52.376684

pokemon-deploy.py

@@ -0,0 +1,36 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+# Define the core prediction function
+def predict_pokemon(image):
+    # Preprocess image
+    print(type(image))
+    image = Image.fromarray(image.astype('uint8'))  # Convert numpy array to PIL image
+    image = image.resize((150, 150)) #resize the image to 150x150
+    image = np.array(image)
+    image = np.expand_dims(image, axis=0) # same as image[None, ...]
+    
+    # Predict
+    prediction = model.predict(image)
+    
+    # Apply softmax to get probabilities for each class
+    prediction = tf.nn.softmax(prediction)
+    
+    # Create a dictionary with the probabilities for each Pokemon
+    evee = np.round(float(prediction[0][0]), 2)
+    farfetched = np.round(float(prediction[0][1]), 2)
+    graveler = np.round(float(prediction[0][2]), 2)
+    venonta = np.round(float(prediction[0][3]), 2)
+    
+    return {'Evee': evee, 'Farfetched': farfetched, 'Graveler': graveler, 'Venonta': venonta}
+
+
+input_image = gr.Image()
+iface = gr.Interface(
+    fn=predict_pokemon,
+    inputs=input_image, 
+    outputs=gr.Label(),
+    description="A simple mlp classification model for image classification using the mnist dataset.")
+iface.launch(share=True)

pokemon-predict-model_transferlearning.keras

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a093367124dc9a2abcfb1a1ec57a7c8641ed2b277e875e2f532b6b94cdf52079
+size 250584780

requirements.txt

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+tensorflow==2.16.1