Update app.py

app.py

@@ -16,6 +16,9 @@ import clip
 
 from PIL import Image
 
+from fastai.vision.all import *
+import skimage
+
 from huggingface_hub import hf_hub_download
 ckpt = hf_hub_download(repo_id="lambdalabs/image-mixer", filename="image-mixer-pruned.ckpt", cache_dir="/data/.cache")
 config = hf_hub_download(repo_id="lambdalabs/image-mixer", filename="image-mixer-config.yaml", cache_dir="/data/.cache")
@@ -25,6 +28,8 @@ model = load_model_from_config(config, ckpt, device=device, verbose=False)
 model = model.to(device).half()
 
 clip_model, preprocess = clip.load("ViT-L/14", device=device)
+gender_learn = load_learner('model.pkl')
+gender_labels = gender_learn.dls.vocab
 
 n_inputs = 5
 
@@ -115,10 +120,16 @@ def run_image_mixer(args):
     torch.cuda.empty_cache()
     return ims[0]
 
+def guess_gender(img):
+    pred,pred_idx,probs = gender_learn.predict(img)
+    return {gender_labels[i]: float(probs[i]) for i in range(len(gender_labels))}
+
 
 import gradio
 
 def boutsify(person):
+    print(guess_gender(person))
+    
     inputs = [
         "Image", "Image", "Text/URL", "Image", "Nothing",
         "","","flowers","","",
@@ -131,10 +142,10 @@ def boutsify(person):
         3.0, 1, 0, 40,
     ]
     
-    return run(inputs)
+    return run_image_mixer(inputs)
 
 gradio_interface = gradio.Interface(
-    fn=my_inference_function,
+    fn=boutsify,
     inputs="image",
     outputs="image",
     title="Boutsify images",