Using a new model trained on 224x224 images

Retrained resnet34 using the same FER203 dataset, but
resized these images to 224x224 - these are what the original
model expects, and the accuracy is a bit better, with no data
cleaning steps.

Also, most images people will upload will be higher resolution
so using 224x224 pixels will give better results than using 48x48.

app.py

@@ -1,8 +1,9 @@
 import gradio as gr
 from fastai.vision.all import *
 import cv2
+import PIL
 
-learn = load_learner('model-v4.pkl')
+learn = load_learner('fec224-resnet34-v1.pkl')
 labels = learn.dls.vocab
 def predict(img):
     image = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY, dstCn=3 )
@@ -12,6 +13,6 @@ def predict(img):
 title = "Facial Expression Classifier"
 description = "A facial expression classifier, trained using the <a href='https://www.kaggle.com/datasets/msambare/fer2013'>FER-2013 dataset</a>. This dataset consists of 28,709 examples of faces: each one is 48x48 grayscale pixels and is labelled with one of the following expressions: anger, disgust, fear, happy, neutral, sad, surprise.<p><p>This was used to train a resnet34 model."
 examples = ["angryExample.jpg", "disgustExample.jpg", "fearExample.jpg", "happyExample.jpg", "neutralExample.jpg", "sadExample.jpg", "surpriseExample.jpg"]
-iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(48,48)), outputs=gr.outputs.Label(num_top_classes=3), examples=examples, title=title, description=description,interpretation='default')
+iface = gr.Interface(fn=predict, inputs=gr.inputs.Image(shape=(224,224)), outputs=gr.outputs.Label(num_top_classes=3), examples=examples, title=title, description=description,interpretation='default')
 iface.launch()
 

environment.yaml

@@ -0,0 +1,203 @@
+name: fastai
+channels:
+  - fastai
+  - defaults
+dependencies:
+  - _libgcc_mutex=0.1=main
+  - _openmp_mutex=5.1=1_gnu
+  - _pytorch_select=0.2=gpu_0
+  - blas=1.0=mkl
+  - blosc=1.21.0=h8c45485_0
+  - bottleneck=1.3.4=py39hce1f21e_0
+  - brotli=1.0.9=h5eee18b_7
+  - brotli-bin=1.0.9=h5eee18b_7
+  - brotlipy=0.7.0=py39h27cfd23_1003
+  - brunsli=0.1=h2531618_0
+  - bzip2=1.0.8=h7b6447c_0
+  - c-ares=1.18.1=h7f8727e_0
+  - ca-certificates=2022.10.11=h06a4308_0
+  - catalogue=2.0.7=py39h06a4308_0
+  - certifi=2022.12.7=py39h06a4308_0
+  - cffi=1.15.1=py39h74dc2b5_0
+  - cfitsio=3.470=h5893167_7
+  - charls=2.2.0=h2531618_0
+  - charset-normalizer=2.0.4=pyhd3eb1b0_0
+  - click=8.0.4=py39h06a4308_0
+  - cloudpickle=2.0.0=pyhd3eb1b0_0
+  - colorama=0.4.6=py39h06a4308_0
+  - cryptography=38.0.1=py39h9ce1e76_0
+  - cycler=0.11.0=pyhd3eb1b0_0
+  - cymem=2.0.6=py39h295c915_0
+  - cython-blis=0.7.7=py39hce1f21e_0
+  - cytoolz=0.11.0=py39h27cfd23_0
+  - dask-core=2022.7.0=py39h06a4308_0
+  - dbus=1.13.18=hb2f20db_0
+  - expat=2.4.4=h295c915_0
+  - fastcore=1.5.27=py_0
+  - fastdownload=0.0.7=py_0
+  - fastprogress=1.0.3=py_0
+  - fftw=3.3.9=h27cfd23_1
+  - flit-core=3.6.0=pyhd3eb1b0_0
+  - fontconfig=2.13.1=h6c09931_0
+  - fonttools=4.25.0=pyhd3eb1b0_0
+  - freetype=2.11.0=h70c0345_0
+  - fsspec=2022.11.0=py39h06a4308_0
+  - future=0.18.2=py39h06a4308_1
+  - giflib=5.2.1=h7b6447c_0
+  - glib=2.69.1=h4ff587b_1
+  - gst-plugins-base=1.14.0=h8213a91_2
+  - gstreamer=1.14.0=h28cd5cc_2
+  - icu=58.2=he6710b0_3
+  - idna=3.4=py39h06a4308_0
+  - imagecodecs=2021.8.26=py39h4cda21f_0
+  - intel-openmp=2021.4.0=h06a4308_3561
+  - jinja2=3.1.2=py39h06a4308_0
+  - joblib=1.1.1=py39h06a4308_0
+  - jpeg=9e=h7f8727e_0
+  - jxrlib=1.1=h7b6447c_2
+  - kiwisolver=1.4.2=py39h295c915_0
+  - krb5=1.19.2=hac12032_0
+  - langcodes=3.3.0=pyhd3eb1b0_0
+  - lcms2=2.12=h3be6417_0
+  - ld_impl_linux-64=2.38=h1181459_1
+  - lerc=3.0=h295c915_0
+  - libaec=1.0.4=he6710b0_1
+  - libbrotlicommon=1.0.9=h5eee18b_7
+  - libbrotlidec=1.0.9=h5eee18b_7
+  - libbrotlienc=1.0.9=h5eee18b_7
+  - libcurl=7.86.0=h91b91d3_0
+  - libdeflate=1.8=h7f8727e_5
+  - libedit=3.1.20221030=h5eee18b_0
+  - libev=4.33=h7f8727e_1
+  - libffi=3.3=he6710b0_2
+  - libgcc-ng=11.2.0=h1234567_1
+  - libgfortran-ng=11.2.0=h00389a5_1
+  - libgfortran5=11.2.0=h1234567_1
+  - libgomp=11.2.0=h1234567_1
+  - libmklml=2019.0.5=h06a4308_0
+  - libnghttp2=1.46.0=hce63b2e_0
+  - libpng=1.6.37=hbc83047_0
+  - libssh2=1.10.0=h8f2d780_0
+  - libstdcxx-ng=11.2.0=h1234567_1
+  - libtiff=4.2.0=h85742a9_0
+  - libuuid=1.0.3=h7f8727e_2
+  - libwebp=1.2.4=h11a3e52_0
+  - libwebp-base=1.2.4=h5eee18b_0
+  - libxcb=1.15=h7f8727e_0
+  - libxml2=2.9.14=h74e7548_0
+  - libzopfli=1.0.3=he6710b0_0
+  - locket=1.0.0=py39h06a4308_0
+  - lz4-c=1.9.4=h6a678d5_0
+  - markupsafe=2.1.1=py39h7f8727e_0
+  - mkl=2021.4.0=h06a4308_640
+  - mkl-service=2.4.0=py39h7f8727e_0
+  - mkl_fft=1.3.0=py39h54f3939_0
+  - mkl_random=1.0.2=py39h63df603_0
+  - munkres=1.1.4=py_0
+  - murmurhash=1.0.7=py39h295c915_0
+  - ncurses=6.3=h5eee18b_3
+  - networkx=2.8.4=py39h06a4308_0
+  - ninja=1.10.2=h06a4308_5
+  - ninja-base=1.10.2=hd09550d_5
+  - numexpr=2.7.3=py39hb2eb853_0
+  - openjpeg=2.4.0=h3ad879b_0
+  - openssl=1.1.1s=h7f8727e_0
+  - packaging=22.0=py39h06a4308_0
+  - pandas=1.4.2=py39h295c915_0
+  - partd=1.2.0=pyhd3eb1b0_1
+  - pathy=0.6.1=py39h06a4308_0
+  - pcre=8.45=h295c915_0
+  - pip=22.3.1=py39h06a4308_0
+  - preshed=3.0.6=py39h295c915_0
+  - pycparser=2.21=pyhd3eb1b0_0
+  - pyopenssl=22.0.0=pyhd3eb1b0_0
+  - pyparsing=3.0.9=py39h06a4308_0
+  - pyqt=5.9.2=py39h2531618_6
+  - pysocks=1.7.1=py39h06a4308_0
+  - python=3.9.12=h12debd9_1
+  - python-dateutil=2.8.2=pyhd3eb1b0_0
+  - pytz=2022.7=py39h06a4308_0
+  - pywavelets=1.3.0=py39h7f8727e_0
+  - pyyaml=6.0=py39h5eee18b_1
+  - qt=5.9.7=h5867ecd_1
+  - readline=8.2=h5eee18b_0
+  - requests=2.28.1=py39h06a4308_0
+  - scikit-learn=1.0.2=py39h51133e4_1
+  - scipy=1.6.2=py39h91f5cce_0
+  - setuptools=65.5.0=py39h06a4308_0
+  - shellingham=1.5.0=py39h06a4308_0
+  - sip=4.19.13=py39h295c915_0
+  - six=1.16.0=pyhd3eb1b0_1
+  - smart_open=5.2.1=py39h06a4308_0
+  - snappy=1.1.9=h295c915_0
+  - spacy=3.3.0=py39hae6d005_0
+  - spacy-legacy=3.0.9=py39h06a4308_0
+  - spacy-loggers=1.0.1=pyhd3eb1b0_0
+  - sqlite=3.40.0=h5082296_0
+  - srsly=2.4.3=py39h295c915_0
+  - thinc=8.0.15=py39hae6d005_0
+  - threadpoolctl=2.2.0=pyh0d69192_0
+  - tifffile=2021.7.2=pyhd3eb1b0_2
+  - tk=8.6.12=h1ccaba5_0
+  - toolz=0.12.0=py39h06a4308_0
+  - tornado=6.1=py39h27cfd23_0
+  - tqdm=4.64.1=py39h06a4308_0
+  - typer=0.4.1=py39h06a4308_0
+  - typing-extensions=4.4.0=py39h06a4308_0
+  - typing_extensions=4.4.0=py39h06a4308_0
+  - tzdata=2022g=h04d1e81_0
+  - urllib3=1.26.13=py39h06a4308_0
+  - wasabi=0.9.1=py39h06a4308_0
+  - wheel=0.37.1=pyhd3eb1b0_0
+  - xz=5.2.8=h5eee18b_0
+  - yaml=0.2.5=h7b6447c_0
+  - zfp=0.5.5=h295c915_6
+  - zlib=1.2.13=h5eee18b_0
+  - zstd=1.4.9=haebb681_0
+  - pip:
+    - aiohttp==3.8.3
+    - aiosignal==1.3.1
+    - altair==4.2.0
+    - anyio==3.6.2
+    - async-timeout==4.0.2
+    - attrs==22.2.0
+    - contourpy==1.0.6
+    - entrypoints==0.4
+    - fastai==2.7.10
+    - fastapi==0.88.0
+    - ffmpy==0.3.0
+    - frozenlist==1.3.3
+    - gradio==3.15.0
+    - h11==0.14.0
+    - httpcore==0.16.3
+    - httpx==0.23.2
+    - jsonschema==4.17.3
+    - linkify-it-py==1.0.3
+    - markdown-it-py==2.1.0
+    - matplotlib==3.6.2
+    - mdit-py-plugins==0.3.3
+    - mdurl==0.1.2
+    - multidict==6.0.4
+    - numpy==1.22.4
+    - nvidia-cublas-cu11==11.10.3.66
+    - nvidia-cuda-nvrtc-cu11==11.7.99
+    - nvidia-cuda-runtime-cu11==11.7.99
+    - nvidia-cudnn-cu11==8.5.0.96
+    - opencv-python==4.7.0.68
+    - orjson==3.8.3
+    - pillow==9.1.1
+    - pycryptodome==3.16.0
+    - pydantic==1.8.2
+    - pydub==0.25.1
+    - pyrsistent==0.19.3
+    - python-multipart==0.0.5
+    - rfc3986==1.5.0
+    - sniffio==1.3.0
+    - starlette==0.22.0
+    - torch==1.13.1
+    - torchvision==0.14.1
+    - uc-micro-py==1.0.1
+    - uvicorn==0.20.0
+    - websockets==10.4
+    - yarl==1.8.2
+prefix: /home/lbiswas/anaconda3/envs/fastai

fec224-resnet34-v1.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:94be543f9d508f82c5ac7e9e314ec217ae3bfceb515a5e51c7c9c3f65fc910b3
+size 87860517