Upload 10 files

.vscode/settings.json

@@ -0,0 +1,22 @@
+{
+    "workbench.colorCustomizations": {
+        "activityBar.activeBackground": "#65c89b",
+        "activityBar.background": "#65c89b",
+        "activityBar.foreground": "#15202b",
+        "activityBar.inactiveForeground": "#15202b99",
+        "activityBarBadge.background": "#945bc4",
+        "activityBarBadge.foreground": "#e7e7e7",
+        "commandCenter.border": "#15202b99",
+        "sash.hoverBorder": "#65c89b",
+        "statusBar.background": "#42b883",
+        "statusBar.foreground": "#15202b",
+        "statusBarItem.hoverBackground": "#359268",
+        "statusBarItem.remoteBackground": "#42b883",
+        "statusBarItem.remoteForeground": "#15202b",
+        "titleBar.activeBackground": "#42b883",
+        "titleBar.activeForeground": "#15202b",
+        "titleBar.inactiveBackground": "#42b88399",
+        "titleBar.inactiveForeground": "#15202b99"
+    },
+    "peacock.color": "#42b883"
+}

README.md

@@ -1,12 +1,13 @@
----
-title: Gender
-emoji: ⚡
-colorFrom: gray
-colorTo: gray
-sdk: gradio
-sdk_version: 4.37.2
-app_file: app.py
-pinned: false
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: Simple Image Classifier
+emoji: 🤑
+colorFrom: purple
+colorTo: indigo
+sdk: streamlit
+sdk_version: 1.31.0
+app_file: app.py
+pinned: false
+short_description: compare different image classifier models
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -1,116 +1,116 @@
-import streamlit as st
-from transformers import pipeline
-from PIL import Image
-
-MODEL_1 = "google/vit-base-patch16-224"
-MIN_ACEPTABLE_SCORE = 0.1
-MAX_N_LABELS = 5
-MODEL_2 = "nateraw/vit-age-classifier"
-MODELS = [
-            "google/vit-base-patch16-224", #Classifição geral
-            "nateraw/vit-age-classifier", #Classifição de idade
-            "microsoft/resnet-50", #Classifição geral
-            "Falconsai/nsfw_image_detection", #Classifição NSFW
-            "cafeai/cafe_aesthetic", #Classifição de estética
-            "microsoft/resnet-18", #Classifição geral
-            "microsoft/resnet-34", #Classifição geral escolhida pelo copilot 
-            "microsoft/resnet-101", #Classifição geral escolhida pelo copilot 
-            "microsoft/resnet-152", #Classifição geral escolhida pelo copilot
-            "microsoft/swin-tiny-patch4-window7-224",#Classifição geral
-            "-- Reinstated on testing--",
-            "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral
-            "-- New --",
-            "-- Still in the testing process --",
-            "facebook/convnext-large-224", #Classifição geral
-            "timm/resnet50.a1_in1k", #Classifição geral
-            "timm/mobilenetv3_large_100.ra_in1k", #Classifição geral
-            "trpakov/vit-face-expression", #Classifição de expressão facial
-            "rizvandwiki/gender-classification", #Classifição de gênero
-            "#q-future/one-align",  #Classifição geral
-            "LukeJacob2023/nsfw-image-detector", #Classifição NSFW   
-            "vit-base-patch16-224-in21k", #Classifição geral
-            "not-lain/deepfake", #Classifição deepfake
-            "carbon225/vit-base-patch16-224-hentai", #Classifição hentai    
-            "facebook/convnext-base-224-22k-1k", #Classifição geral
-            "facebook/convnext-large-224", #Classifição geral
-            "facebook/convnext-tiny-224",#Classifição geral
-            "nvidia/mit-b0", #Classifição geral
-            "microsoft/resnet-18", #Classifição geral
-            "microsoft/swinv2-base-patch4-window16-256", #Classifição geral
-            "andupets/real-estate-image-classification", #Classifição de imóveis
-            "timm/tf_efficientnetv2_s.in21k", #Classifição geral
-            "timm/convnext_tiny.fb_in22k",
-            "DunnBC22/vit-base-patch16-224-in21k_Human_Activity_Recognition", #Classifição de atividade humana
-            "FatihC/swin-tiny-patch4-window7-224-finetuned-eurosat-watermark", #Classifição geral
-            "aalonso-developer/vit-base-patch16-224-in21k-clothing-classifier", #Classifição de roupas
-            "RickyIG/emotion_face_image_classification", #Classifição de emoções
-            "shadowlilac/aesthetic-shadow" #Classifição de estética
-        ]
-
-def classify(image, model):
-    classifier = pipeline("image-classification", model=model)
-    result= classifier(image)
-    return result
-
-def save_result(result):
-    st.write("In the future, this function will save the result in a database.")
-
-def print_result(result):
-
-    comulative_discarded_score = 0
-    for i in range(len(result)):
-        if result[i]['score'] < MIN_ACEPTABLE_SCORE:
-            comulative_discarded_score += result[i]['score']
-        else:
-            st.write(result[i]['label'])
-            st.progress(result[i]['score'])
-            st.write(result[i]['score'])
-
-    st.write(f"comulative_discarded_score:")
-    st.progress(comulative_discarded_score)
-    st.write(comulative_discarded_score)
-    
-
-
-def main():
-    st.title("Image Classification")
-    st.write("This is a simple web app to test and compare different image classifier models using Hugging Face's image-classification pipeline.")
-    st.write("From time to time more models will be added to the list. If you want to add a model, please open an issue on the GitHub repository.")
-    st.write("If you like this project, please consider liking it or buying me a coffee. It will help me to keep working on this and other projects. Thank you!")
-
-    # Buy me a Coffee Setup
-    bmc_link = "https://www.buymeacoffee.com/nuno.tome" 
-    # image_url = "https://helloimjessa.files.wordpress.com/2021/06/bmc-button.png?w=150" # Image URL
-    image_url = "https://i.giphy.com/RETzc1mj7HpZPuNf3e.webp" # Image URL
-        
-    image_size = "150px" # Image size
-    #image_link_markdown = f"<img src='{image_url}' width='25%'>"
-    image_link_markdown = f"[![Buy Me a Coffee]({image_url})]({bmc_link})"
-
-    #image_link_markdown = f"[![Buy Me a Coffee]({image_url})]({bmc_link})" # Create a clickable image link
-
-    st.markdown(image_link_markdown, unsafe_allow_html=True) # Display the image link
-    # Buy me a Coffee Setup
-    
-    #st.markdown("<img src='https://helloimjessa.files.wordpress.com/2021/06/bmc-button.png?w=1024' width='15%'>", unsafe_allow_html=True)
-  
-    input_image = st.file_uploader("Upload Image")
-    shosen_model = st.selectbox("Select the model to use",  MODELS)
-    
-    
-    if input_image is not None:
-        image_to_classify = Image.open(input_image)
-        st.image(image_to_classify, caption="Uploaded Image")
-        if st.button("Classify"):
-            image_to_classify = Image.open(input_image)
-            classification_obj1 =[]
-            #avable_models = st.selectbox
-            
-            classification_result = classify(image_to_classify, shosen_model)
-            classification_obj1.append(classification_result)
-            print_result(classification_result)
-            save_result(classification_result)
-
-
-if __name__ == "__main__":
+import streamlit as st
+from transformers import pipeline
+from PIL import Image
+
+MODEL_1 = "google/vit-base-patch16-224"
+MIN_ACEPTABLE_SCORE = 0.1
+MAX_N_LABELS = 5
+MODEL_2 = "nateraw/vit-age-classifier"
+MODELS = [
+            "google/vit-base-patch16-224", #Classifição geral
+            "nateraw/vit-age-classifier", #Classifição de idade
+            "microsoft/resnet-50", #Classifição geral
+            "Falconsai/nsfw_image_detection", #Classifição NSFW
+            "cafeai/cafe_aesthetic", #Classifição de estética
+            "microsoft/resnet-18", #Classifição geral
+            "microsoft/resnet-34", #Classifição geral escolhida pelo copilot 
+            "microsoft/resnet-101", #Classifição geral escolhida pelo copilot 
+            "microsoft/resnet-152", #Classifição geral escolhida pelo copilot
+            "microsoft/swin-tiny-patch4-window7-224",#Classifição geral
+            "-- Reinstated on testing--",
+            "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral
+            "-- New --",
+            "-- Still in the testing process --",
+            "facebook/convnext-large-224", #Classifição geral
+            "timm/resnet50.a1_in1k", #Classifição geral
+            "timm/mobilenetv3_large_100.ra_in1k", #Classifição geral
+            "trpakov/vit-face-expression", #Classifição de expressão facial
+            "rizvandwiki/gender-classification", #Classifição de gênero
+            "#q-future/one-align",  #Classifição geral
+            "LukeJacob2023/nsfw-image-detector", #Classifição NSFW   
+            "vit-base-patch16-224-in21k", #Classifição geral
+            "not-lain/deepfake", #Classifição deepfake
+            "carbon225/vit-base-patch16-224-hentai", #Classifição hentai    
+            "facebook/convnext-base-224-22k-1k", #Classifição geral
+            "facebook/convnext-large-224", #Classifição geral
+            "facebook/convnext-tiny-224",#Classifição geral
+            "nvidia/mit-b0", #Classifição geral
+            "microsoft/resnet-18", #Classifição geral
+            "microsoft/swinv2-base-patch4-window16-256", #Classifição geral
+            "andupets/real-estate-image-classification", #Classifição de imóveis
+            "timm/tf_efficientnetv2_s.in21k", #Classifição geral
+            "timm/convnext_tiny.fb_in22k",
+            "DunnBC22/vit-base-patch16-224-in21k_Human_Activity_Recognition", #Classifição de atividade humana
+            "FatihC/swin-tiny-patch4-window7-224-finetuned-eurosat-watermark", #Classifição geral
+            "aalonso-developer/vit-base-patch16-224-in21k-clothing-classifier", #Classifição de roupas
+            "RickyIG/emotion_face_image_classification", #Classifição de emoções
+            "shadowlilac/aesthetic-shadow" #Classifição de estética
+        ]
+
+def classify(image, model):
+    classifier = pipeline("image-classification", model=model)
+    result= classifier(image)
+    return result
+
+def save_result(result):
+    st.write("In the future, this function will save the result in a database.")
+
+def print_result(result):
+
+    comulative_discarded_score = 0
+    for i in range(len(result)):
+        if result[i]['score'] < MIN_ACEPTABLE_SCORE:
+            comulative_discarded_score += result[i]['score']
+        else:
+            st.write(result[i]['label'])
+            st.progress(result[i]['score'])
+            st.write(result[i]['score'])
+
+    st.write(f"comulative_discarded_score:")
+    st.progress(comulative_discarded_score)
+    st.write(comulative_discarded_score)
+    
+
+
+def main():
+    st.title("Image Classification")
+    st.write("This is a simple web app to test and compare different image classifier models using Hugging Face's image-classification pipeline.")
+    st.write("From time to time more models will be added to the list. If you want to add a model, please open an issue on the GitHub repository.")
+    st.write("If you like this project, please consider liking it or buying me a coffee. It will help me to keep working on this and other projects. Thank you!")
+
+    # Buy me a Coffee Setup
+    bmc_link = "https://www.buymeacoffee.com/nuno.tome" 
+    # image_url = "https://helloimjessa.files.wordpress.com/2021/06/bmc-button.png?w=150" # Image URL
+    image_url = "https://i.giphy.com/RETzc1mj7HpZPuNf3e.webp" # Image URL
+        
+    image_size = "150px" # Image size
+    #image_link_markdown = f"<img src='{image_url}' width='25%'>"
+    image_link_markdown = f"[![Buy Me a Coffee]({image_url})]({bmc_link})"
+
+    #image_link_markdown = f"[![Buy Me a Coffee]({image_url})]({bmc_link})" # Create a clickable image link
+
+    st.markdown(image_link_markdown, unsafe_allow_html=True) # Display the image link
+    # Buy me a Coffee Setup
+    
+    #st.markdown("<img src='https://helloimjessa.files.wordpress.com/2021/06/bmc-button.png?w=1024' width='15%'>", unsafe_allow_html=True)
+  
+    input_image = st.file_uploader("Upload Image")
+    shosen_model = st.selectbox("Select the model to use",  MODELS)
+    
+    
+    if input_image is not None:
+        image_to_classify = Image.open(input_image)
+        st.image(image_to_classify, caption="Uploaded Image")
+        if st.button("Classify"):
+            image_to_classify = Image.open(input_image)
+            classification_obj1 =[]
+            #avable_models = st.selectbox
+            
+            classification_result = classify(image_to_classify, shosen_model)
+            classification_obj1.append(classification_result)
+            print_result(classification_result)
+            save_result(classification_result)
+
+
+if __name__ == "__main__":
     main()

huggingface.co-spaces-Nunt-simple_image_classifier.url

@@ -0,0 +1,5 @@
+[{000214A0-0000-0000-C000-000000000046}]
+Prop3=19,11
+[InternetShortcut]
+IDList=
+URL=https://huggingface.co/spaces/Nunt/simple_image_classifier

moldel_log,txt

@@ -0,0 +1,66 @@
+2024-02-03 ------------------------------------------------------------------
+In error:
+    #NOT OK "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral
+    #NOT OK "timm/vit_large_patch14_clip_224.openai_ft_in12k_in1k", #Classifição geral
+    #NOT OK "timm/vit_base_patch16_224_in21k", #Classifição geral escolhida pelo copilot 
+    #NOT OK "microsoft/resnet-50-kinetics-400", #Classifição geral escolhida pelo copilot
+
+----
+
+    "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral
+        ok
+        TODO: reintroduce to test
+
+    "timm/vit_large_patch14_clip_224.openai_ft_in12k_in1k", #Classifição geral
+        ok
+        other layout
+        TODO: adapt
+
+    "timm/vit_base_patch16_224_in21k", #Classifição geral escolhida pelo copilot
+        off-line
+
+    "microsoft/resnet-50-kinetics-400", #Classifição geral escolhida pelo copilot
+        off-line
+
+---
+
+    model/del/microsoft_resnet-50-kinetics-400
+    model/add/microsoft_beit-base-patch16-224-pt22k-ft22k
+        "microsoft/beit-base-patch16-224-pt22k-ft22k", #Classifição geral
+
+---
+
+    models to add
+        Laxhar/anime_aesthetic_variant
+            in error but test
+
+        apple/ml-aim.git
+            sem tester online 
+
+        new:"
+
+"
+"
+            
+
+            https://huggingface.co/timm/fastvit_ma36.apple_dist_in1k
+
+
+
+            fancyfeast/joytag
+                in error but test
+            
+    test:
+        https://huggingface.co/spaces/teowu/OneScorer
+
+    can have use
+        https://huggingface.co/spaces/AnnasBlackHat/Image-Similarity
+        https://huggingface.co/spaces/omerXfaruq/FindYourTwins
+        https://huggingface.co/spaces/Woleek/image-based-soundtrack-generation
+        https://huggingface.co/chbh7051/vit-final-driver-drowsiness-detection
+
+
+colonoscopia
+
+https://huggingface.co/mrm8488/vit-base-patch16-224_finetuned-kvasirv2-colonoscopy
+huggingface.co/DunnBC22/vit-base-patch16-224-in21k_covid_19_ct_scans         

nunt-simple-image-classifier.hf.space.url

@@ -0,0 +1,5 @@
+[{000214A0-0000-0000-C000-000000000046}]
+Prop3=19,11
+[InternetShortcut]
+IDList=
+URL=https://nunt-simple-image-classifier.hf.space/

requirements.txt

@@ -1,3 +1,3 @@
-streamlit
-torch
+streamlit
+torch
 transformers

simple_image_classifier.code-workspace

@@ -0,0 +1,29 @@
+{
+	"folders": [
+		{
+			"path": "."
+		}
+	],
+	"settings": {
+		"workbench.colorCustomizations": {
+			"activityBar.activeBackground": "#6ce19f",
+			"activityBar.background": "#6ce19f",
+			"activityBar.foreground": "#15202b",
+			"activityBar.inactiveForeground": "#15202b99",
+			"activityBarBadge.background": "#9760df",
+			"activityBarBadge.foreground": "#e7e7e7",
+			"commandCenter.border": "#15202b99",
+			"sash.hoverBorder": "#6ce19f",
+			"statusBar.background": "#42d883",
+			"statusBar.foreground": "#15202b",
+			"statusBarItem.hoverBackground": "#28bf69",
+			"statusBarItem.remoteBackground": "#42d883",
+			"statusBarItem.remoteForeground": "#15202b",
+			"titleBar.activeBackground": "#42d883",
+			"titleBar.activeForeground": "#15202b",
+			"titleBar.inactiveBackground": "#42d88399",
+			"titleBar.inactiveForeground": "#15202b99"
+		},
+		"peacock.color": "#42d883"
+	}
+}